Avalanche (WB Studios)

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. As Sr. Staff – Data Science & Applied AI (Gen AI), you will be a core technical contributor within WBD’s AI Center of Excellence (CoE). This role is designed for a hands-on senior architect who operates at the intersection of enterprise architecture, applied AI, Generative AI, agentic AI, and cloud platform engineering. You will translate complex business challenges into scalable AI solution architectures, production-ready platforms, and reusable technical patterns that drive measurable enterprise value. You will serve as a senior individual contributor, partnering closely with Product, Engineering, Data, Security, and Business stakeholders to design, govern, and scale modern AI solutions across the organization. The role combines solution architecture leadership with deep expertise in GenAI application design, agentic systems, and AI cloud architecture on AWS and Snowflake. Enterprise AI Solution Architecture - Define end-to-end solution architecture for enterprise AI, GenAI, and agentic AI applications aligned to business and technology strategy. - Translate business workflows and operational challenges into scalable AI solution patterns, including autonomous and semi-autonomous agent use cases. - Partner with product, engineering, data, and business teams to move AI and GenAI use cases from concept and pilot into production at enterprise scale. - Create reusable architecture patterns, accelerators, reference implementations, and technical standards to speed AI adoption across teams. Generative AI & LLM Applications - Architect scalable GenAI applications for use cases such as enterprise copilots, semantic search, summarization, metadata enrichment, content intelligence, and document processing. - Define reference architectures for Retrieval-Augmented Generation (RAG), prompt orchestration, model selection, context management, and response quality optimization. - Develop and standardize evaluation frameworks to assess hallucination risk, answer quality, latency, cost efficiency, safety, and business relevance. - Implement responsible AI controls, safety mechanisms, and governance practices to ensure compliant and reliable deployment of GenAI systems. - Evaluate and recommend foundation models, embeddings, prompt strategies, and adaptation approaches based on business fit, performance, and cost. Productionization, Engineering & Governance - Collaborate with Data Engineering, Platform Engineering, DevOps, and Security teams to productionize AI and GenAI solutions in scalable cloud environments. - Design CI/CD and automation patterns for model deployment, prompt/version management, testing, release control, and operational support. - Implement monitoring for model drift, prompt drift, performance degradation, usage patterns, system health, and data integrity. - Support governance, risk management, and responsible AI initiatives by embedding security, privacy, compliance, and auditability into solution design. - Innovation & Technical Leadership - Stay current with advancements in foundation models, multimodal AI, agent frameworks, orchestration patterns, and cloud-native AI services. - Provide architecture guidance, design reviews, and technical mentorship across cross-functional teams. - Contribute to enterprise-wide AI best practices, reusable frameworks, and technical decision-making to elevate the maturity of the AI ecosystem. Qualifications & Experiences: - Bachelor’s degree, Master’s degree, or higher in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline. - 8+ years of relevant experience in solution architecture, data science, machine learning, or AI engineering, with at least 2+ years of experience in Generative AI / LLM-based solutions. - Demonstrated track record of designing and delivering production-grade AI/ML/GenAI solutions with measurable business impact. - Strong experience in architecting enterprise AI solutions across business workflows, data ecosystems, and cloud platforms. - Hands-on expertise in building and scaling GenAI and LLM applications, including prompt engineering, RAG architectures, semantic search, embeddings, and evaluation frameworks. - Experience designing or supporting agentic AI systems, including orchestration, tool usage, memory, guardrails, and human oversight patterns. - Deep understanding of cloud-native AI/ML architecture principles, including deployment patterns, platform reliability, observability, security, and cost optimization. - Experience establishing reusable architecture patterns, technical standards, and governance controls for AI systems in enterprise environments. - Strong collaboration skills with Product, Engineering, Data, Security, and Business teams in global, cross-functional settings. Generative AI & Large Language Model (LLM) Expertise - Hands-on experience designing and deploying Generative AI solutions using large language models (e.g., GPT-class models, open-source foundation models, or enterprise LLM platforms). - Strong proficiency in prompt engineering, structured output design, few-shot learning strategies, and systematic prompt optimization. - Experience building Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise data sources. - Familiarity with embedding models, semantic search, and vector stores (e.g., Pinecone, Weaviate, OpenSearch, FAISS, or equivalent). - Experience fine-tuning or adapting foundation models using parameter-efficient approaches (e.g., LoRA, adapters, instruction tuning). - Understanding of LLM evaluation methodologies, including hallucination detection, bias assessment, response quality scoring, and cost-performance trade-offs. - Exposure to multimodal AI (text, image, audio, video) and agent-based workflows is a plus. - Experience working with enterprise AI platforms (e.g., AWS Bedrock, Azure OpenAI, Databricks Model Serving, Snowflake Cortex, or equivalent). - Understanding of Responsible AI principles, data privacy considerations, and model governance requirements in regulated environments. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN. To see what it’s like to work at CNN, follow @WBDLife on  Instagram  and  X ! Your New Role We are CNN. THE WORLD'S MOST ESSENTIAL AND ENGAGING SOURCE OF DIGITAL NEWS. We are in the midst of rapid transformation and need our next generation of innovators, makers, and dreamers who will lead and drive our growth. We aim to make the world a better, more connected place. CNN is looking for a Principal Product Designer to lead our consumer AI experiences across user-facing digital platforms. This is a senior level individual contributor role that will lead design innovation on our high-impact digital surfaces through smart and delightful AI features. The ideal candidate is an experienced designer, who will incorporate their deep fluency in AI technologies and passion for news media to shape new ways for our consumers to engage with the news. You’ll collaborate closely with design across the org, Product, Engineering, Editorial, UXR and Analytics teams. Your Role Accountabilities - You will be an integral part of CNN’s design team, developing and steering a bold user experience vision for evolving consumer experiences through delightful AI features, from content discovery to comprehension to personalization. - You will collaborate closely with your Product partner on a roadmap that prioritizes high-impact features that deepen engagement and enhance the end users’ experiences, from personalized feeds to dynamic homepages to conversational agents that allow users to better understand the news. - Your work will include identifying user needs, producing cutting-edge user experiences, conducting rapid prototyping to iteratively test and validate product features and see new features and enhancements through launch. - You will partner closely with other designers and design leaders on driving an innovative design vision while ensuring AI features feel seamless, natural, and cohesive across surfaces and platforms. - You will guide the overall UX strategy for consumer AI experiences, with user research and analytics data, to develop a deep understanding of how users engage, what matters to them, and identify designs that uniquely solve pain points and move key business metrics. - You will serve as a thought leader for ethical and responsible AI design. You understand the media landscape, and you are innovative, and committed to pushing the boundaries of CNN. Qualifications & Experience - 12+ years' related work experience in product design with a proven track record of launching innovative consumer-facing products - 3+ years working with AI/ML technologies, including experience with large language models, recommendations systems, or generative interfaces. - Strong understanding of AI fundamentals and their application in product experiences; comfort partnering with technical leads and data scientists. Experience in media companies is a plus. - Expertise in Figma, prototyping and a deep knowledge of utilizing design systems; extensive experience in program management tools such as Confluence and Jira. - Impeccable written and verbal communication, facilitation, and interpersonal skills, and a proven track record of executing a design vision and leading through influence cross-functionally. - Data-driven, with extensive experience testing and refining to continually improve upon metrics. - Mastery of best UX design practices, including usability principles, user research methodologies and testing techniques. - Bachelor's degree in design, human-computer interaction (HCI), or equivalent professional experience. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $189,700.00 - $352,300.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Staff Machine Learning Engineer (Data & Audience Platform), Hyderabad About Warner Bros. Discovery Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet our Team Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role The Staff MLE is the senior-most individual contributor on the Hyderabad ML Engineering team. You will set the technical direction for the team’s most complex and strategically important ML systems, serve as the technical authority across multiple concurrent workstreams, and act as a force multiplier for the entire team. You will own the architecture of WBD’s ML capabilities in Hyderabad — spanning identity intelligence, audience intelligence, content affinity, and forecasting — and be a key technical partner to the Senior ML Engineering Manager and Director. This role requires 8+ years of experience, exceptional depth across the ML stack, and the ability to influence technical decisions across organizational boundaries. What You’ll Do Technical Vision & Architecture - Define and own the technical architecture for the team’s core systems: the probabilistic identity spine, audience intelligence platform, content-affinity and genre-preference models, and ML-based forecasting. - Lead architectural decisions for the team’s MLOps framework — feature-store design, training-pipeline standards, model-serving patterns, and monitoring infrastructure — on a Databricks-first architecture, integrating Snowflake and AWS SageMaker where each is the right tool. - Evaluate and recommend new technologies and approaches (e.g., DCR-native modeling, graph ML, agentic ML orchestration, LLM-augmented pipelines) with clear build/buy/partner assessments. - Drive standardization of ML practices across Hyderabad and align with global WBD ML engineering standards. Flagship ML System Ownership - Architect and lead delivery of the probabilistic identity resolution system — resolving unauthenticated device IDs and 1P cookies to households/persons with calibrated confidence at scale across all WBD brands — using entity resolution, embeddings/representation learning, calibration, candidate blocking, and champion/challenger promotion, with a roadmap toward person-level graphs (incl. GNNs) and real-time resolution. - Lead the evolution of Audience Intelligence : ML Promo Optimizer (layered retrieval + propensity + closed-loop measurement, toward mixture-of-experts), STAT v2 (two-tower single-title affinity with semantic content embeddings), lookalike modeling (LAL 2.0+) inside Snowflake DCR, and content segmentation. - Own the ML architecture for forecasting (audience growth, demand, yield/pricing) and ensure models are production-grade, monitored, and continuously improved. - Drive the roadmap for bringing ML personalization signals (genre/content affinity, engagement trends) into batch and, over time, real-time activation paths. MLOps Platform Leadership - Define the team’s MLOps target architecture: feature contracts, model-registry governance, automated retraining, drift detection, and A/B experimentation infrastructure. - Establish engineering standards for the full ML lifecycle: data contracts → feature engineering → training → evaluation → deployment → monitoring → deprecation. - Champion a lightweight, adoptable, well-documented architecture (Databricks Asset Bundles, GitHub Actions CI/CD, MLflow throughout, feature tables, inference/monitoring tables), with leakage prevention, reproducibility, and FinOps controls baked in. Agentic AI & Emerging Capabilities - Lead the team’s adoption of agentic AI development: define standards for using Cursor, GitHub Copilot, and Amazon Q in production ML workflows, and for MCP-based tooling. - Architect the team’s use of Databricks Genie at scale — Genie Space governance, Unity Catalog semantic-layer standards, and knowledge-store curation — so ML outputs (audience scores, identity confidence, affinity signals) are self-serviceable by Marketing, Ad Sales, and Product without engineering intervention. - Own the team’s Snowflake Cortex strategy — Cortex Analyst / Copilot embedded into internal tooling, Cortex Search for RAG-based internal knowledge, and (where valuable) Cortex Fine-Tuning on WBD audience/identity vocabulary. - Architect agentic ML workflows for high-value automation (feature-selection and hyperparameter agents, data-quality monitoring agents, model-card generation) and evaluate emerging paradigms (DCR-native training, real-time feature serving) for the production roadmap. Organizational Influence & Mentorship - Serve as the technical anchor for Hyderabad; provide architectural guidance and deep mentorship to Senior and MLE 2 engineers. - Partner with the Senior ML Engineering Manager on technical roadmap prioritization, headcount planning, and team capability development. - Represent the Hyderabad team in cross-functional technical forums with US-based ML, Data Engineering, Product, and Ad Sales stakeholders. - Produce high-quality technical design documents, architecture reviews, and post-mortems that elevate the team’s engineering culture. What You’ll Bring Required - 8+ years of industry experience in ML engineering (6+ with a Ph.D.), with demonstrated Staff-level scope and impact. - Mastery of the full ML stack: data engineering, feature engineering, model development, MLOps, and production monitoring. - Deep Databricks expertise: Delta Lake, Unity Catalog, Workflows/DLT, MLflow, Feature Store, Asset Bundles, and Genie Space configuration. - Strong AWS proficiency (SageMaker training/pipelines/model registry, S3, Lambda, Glue) and Snowflake expertise (DCR patterns, Snowpark, Cortex, SQL optimization at scale). - Proven experience architecting production ML systems serving millions of users, and a track record of technical leadership (setting standards, driving architecture, influencing across teams). - Expert proficiency with ML frameworks (PyTorch, TensorFlow, XGBoost/LightGBM, scikit-learn) and deep understanding of statistics and ML fundamentals. - Master’s or Ph.D. in Computer Science, Statistics, Machine Learning, or a related field (or equivalent industry experience). - Excellent communication, with the ability to advocate technical solutions to engineering, science, product, and executive audiences. Preferred - Streaming / media / ad-tech ML: identity resolution, audience modeling, recommendation/ranking, content understanding. - Deep knowledge of probabilistic identity resolution (entity resolution, graph-based household matching, confidence calibration) and Data Clean Room ML (Snowflake DCR, AWS Clean Rooms). - Hands-on experience with agentic AI frameworks at production scale (LangGraph, AutoGen, MCP, CrewAI), Databricks Genie Space curation, and Snowflake Cortex Search / Fine-Tuning for enterprise RAG. - Experience with real-time feature serving and low-latency inference, and with mixture-of-experts or graph neural networks. - Published research or conference presentations in relevant ML domains. Our Technology Stack Primary platform: Databricks (Lakehouse, PySpark, Delta, Workflows/DLT, MLflow, Feature Store, Unity Catalog, Asset Bundles, Genie). Cloud: AWS (SageMaker, S3, Lambda, Glue). Warehouse: Snowflake (DCR, Snowpark, Cortex). Activation: Mosaic, FreeWheel, Google Ad Manager. Agentic AI: Cursor, GitHub Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, MCP. Languages: Python (primary), SQL, Scala (as needed). What We Offer: - A Great Place to work - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Senior Machine Learning Engineer (Data & Audience Platform), Hyderabad About Warner Bros. Discovery Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet our Team Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role As a Senior MLE, you will own the design and delivery of production ML systems that directly impact audience targeting, advertising revenue, subscriber engagement, and retention across WBD’s global portfolio. You will lead technical execution on key workstreams — including probabilistic identity resolution, lookalike modeling, single-title affinity, and forecasting — while mentoring MLE 2s and collaborating closely with Staff MLEs and product stakeholders. This is a high-ownership role for engineers with roughly 5–8 years of experience who can independently drive a project from problem framing through production deployment and monitoring. What You’ll Do ML System Design & Ownership - Lead end-to-end development of production ML systems: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring. - Own key ML products such as probabilistic identity resolution (matching unauthenticated device IDs and 1P cookies to households/persons with calibrated confidence), single-title affinity (e.g., STAT two-tower retrieval), and audience/propensity models. - Design scalable feature pipelines on Databricks (PySpark, Delta, Workflows/DLT, Unity Catalog) and the WBD feature store, with documented feature contracts, backfill paths, and freshness SLAs. - Architect batch and near-real-time inference pipelines integrated with Snowflake and activation systems (Mosaic, FreeWheel, GAM). Modeling & Experimentation - Develop and optimize models across the ML spectrum: gradient boosting (XGBoost/LightGBM), embedding/two-tower retrieval, neural ranking, probability calibration (e.g., isotonic regression), and probabilistic/graph-based matching. - Design rigorous offline and online experiments; define evaluation frameworks (precision/recall, AUC-ROC, NDCG, decile lift, calibration curves) appropriate to each use case. - Apply causal-inference techniques (propensity scoring, uplift/incrementality modeling) to measure true lift of audience targeting on engagement and retention KPIs. - Contribute to lookalike modeling (LAL 2.0+) using 1,000+ first- and third-party features, including privacy-safe builds inside Data Clean Rooms (Snowflake DCR). MLOps & Infrastructure - Champion MLOps best practices: model versioning, champion/challenger promotion, automated retraining triggers, drift detection, and production monitoring with MLflow on Databricks. - Build and maintain robust, reproducible, auditable ML pipelines on Databricks (and AWS SageMaker where appropriate, e.g., the identity-resolution track); enforce leakage prevention and training/serving consistency. - Contribute to the team’s feature-store strategy — feature contracts, backfills, and freshness SLAs — and implement data-quality checks, model-health dashboards, and alerting thresholds. - Embed FinOps cost discipline (compute caps, auto-termination, job tagging) into pipeline design. Agentic AI & Modern Development - Actively use and advocate for AI-assisted development: Cursor, GitHub Copilot, and Amazon Q for code generation, review, and documentation. - Leverage Databricks Genie as a governed natural-language analytics layer — configuring Genie Spaces over ML feature tables and audience datasets to enable self-service exploration for cross-functional stakeholders. - Use Snowflake Cortex (Copilot, Cortex Analyst, Cortex Search) to accelerate SQL authoring, data discovery, and RAG-based internal tooling over Snowflake-resident identity and audience data. - Prototype agentic ML workflows (e.g., with MCP-compatible tooling, LangChain/LangGraph) to automate repetitive tasks such as data validation, feature selection, and hyperparameter search; evaluate LLM-based approaches for metadata enrichment and content understanding. Mentorship & Cross-functional Collaboration - Mentor MLE 2s through code reviews, design discussions, and pairing; contribute to team technical standards. - Partner with Product, Marketing, and Ad Sales to translate business requirements into ML problem formulations, and with Data Engineering on data contracts and pipeline SLAs. - Communicate model performance, trade-offs, and business impact clearly to technical and non-technical stakeholders. Flagship Projects You’ll Work On - Identity Intelligence — foundational, privacy-safe identity across all WBD brands: probabilistic ID resolution that resolves unauthenticated signals to households/persons with calibrated confidence (entity resolution with gradient boosting and embeddings, representation learning, isotonic calibration, candidate blocking, champion/challenger pipelines), expanding addressable audiences beyond deterministic matching. - Audience Intelligence — advertising and marketing use cases: lookalike and predictive audiences (LAL across 1,000+ features), ML-driven smart audiences, layered retrieval + propensity, and incrementality/closed-loop optimization, with privacy-safe activation including data clean rooms. - ML-based Forecasting — audience growth, demand, and advertising yield/pricing forecasting that powers ad sales and marketing decisions. - Content Preferences & Affinity — genre-preference, content-preference, and single-title affinity modeling (two-tower retrieval with semantic content embeddings) that ranks audiences for upcoming titles and powers cross-channel promotion. What You’ll Bring Required - 5–8 years of industry experience in ML engineering or applied data science (3+ years with a Ph.D.). - Deep Python expertise and production-quality software engineering practices; production experience building and deploying ML at scale (millions+ of users/records). - Strong proficiency in Databricks (PySpark, Delta Lake, Workflows/DLT, MLflow, Unity Catalog) and solid SQL/Snowflake experience for feature sourcing and model-output delivery. - Experience with AWS ML services (SageMaker, S3, Lambda). - Strong understanding of ML model evaluation, A/B testing, and statistical inference; knowledge in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, causal/interpretable ML, forecasting, bandits, or optimization. - Demonstrated ability to lead technical decisions and mentor engineers. - Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent experience). - Excellent written and verbal communication, with the ability to advocate technical solutions to engineers, scientists, and product stakeholders. Preferred - Recommendation systems, personalization, identity resolution, or audience modeling in a media / streaming / ad-tech context. - Familiarity with Data Clean Room environments (Snowflake DCR, AWS Clean Rooms) and consent-aware activation. - Experience with two-tower / retrieval architectures, probabilistic identity resolution (graph-based matching, entity resolution), and probability calibration. - Hands-on experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, MCP), Databricks Genie Space configuration, and Snowflake Cortex. - Experience with feature stores (Databricks Feature Store, Tecton, Feast) and contributions to open source or ML publications. What We Offer: - A Great Place to work - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Senior Machine Learning Engineer (Data & Audience Platform), Hyderabad About Warner Bros. Discovery Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet our Team Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role As a Senior MLE, you will own the design and delivery of production ML systems that directly impact audience targeting, advertising revenue, subscriber engagement, and retention across WBD’s global portfolio. You will lead technical execution on key workstreams — including probabilistic identity resolution, lookalike modeling, single-title affinity, and forecasting — while mentoring MLE 2s and collaborating closely with Staff MLEs and product stakeholders. This is a high-ownership role for engineers with roughly 5–8 years of experience who can independently drive a project from problem framing through production deployment and monitoring. What You’ll Do ML System Design & Ownership - Lead end-to-end development of production ML systems: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring. - Own key ML products such as probabilistic identity resolution (matching unauthenticated device IDs and 1P cookies to households/persons with calibrated confidence), single-title affinity (e.g., STAT two-tower retrieval), and audience/propensity models. - Design scalable feature pipelines on Databricks (PySpark, Delta, Workflows/DLT, Unity Catalog) and the WBD feature store, with documented feature contracts, backfill paths, and freshness SLAs. - Architect batch and near-real-time inference pipelines integrated with Snowflake and activation systems (Mosaic, FreeWheel, GAM). Modeling & Experimentation - Develop and optimize models across the ML spectrum: gradient boosting (XGBoost/LightGBM), embedding/two-tower retrieval, neural ranking, probability calibration (e.g., isotonic regression), and probabilistic/graph-based matching. - Design rigorous offline and online experiments; define evaluation frameworks (precision/recall, AUC-ROC, NDCG, decile lift, calibration curves) appropriate to each use case. - Apply causal-inference techniques (propensity scoring, uplift/incrementality modeling) to measure true lift of audience targeting on engagement and retention KPIs. - Contribute to lookalike modeling (LAL 2.0+) using 1,000+ first- and third-party features, including privacy-safe builds inside Data Clean Rooms (Snowflake DCR). MLOps & Infrastructure - Champion MLOps best practices: model versioning, champion/challenger promotion, automated retraining triggers, drift detection, and production monitoring with MLflow on Databricks. - Build and maintain robust, reproducible, auditable ML pipelines on Databricks (and AWS SageMaker where appropriate, e.g., the identity-resolution track); enforce leakage prevention and training/serving consistency. - Contribute to the team’s feature-store strategy — feature contracts, backfills, and freshness SLAs — and implement data-quality checks, model-health dashboards, and alerting thresholds. - Embed FinOps cost discipline (compute caps, auto-termination, job tagging) into pipeline design. Agentic AI & Modern Development - Actively use and advocate for AI-assisted development: Cursor, GitHub Copilot, and Amazon Q for code generation, review, and documentation. - Leverage Databricks Genie as a governed natural-language analytics layer — configuring Genie Spaces over ML feature tables and audience datasets to enable self-service exploration for cross-functional stakeholders. - Use Snowflake Cortex (Copilot, Cortex Analyst, Cortex Search) to accelerate SQL authoring, data discovery, and RAG-based internal tooling over Snowflake-resident identity and audience data. - Prototype agentic ML workflows (e.g., with MCP-compatible tooling, LangChain/LangGraph) to automate repetitive tasks such as data validation, feature selection, and hyperparameter search; evaluate LLM-based approaches for metadata enrichment and content understanding. Mentorship & Cross-functional Collaboration - Mentor MLE 2s through code reviews, design discussions, and pairing; contribute to team technical standards. - Partner with Product, Marketing, and Ad Sales to translate business requirements into ML problem formulations, and with Data Engineering on data contracts and pipeline SLAs. - Communicate model performance, trade-offs, and business impact clearly to technical and non-technical stakeholders. Flagship Projects You’ll Work On - Identity Intelligence — foundational, privacy-safe identity across all WBD brands: probabilistic ID resolution that resolves unauthenticated signals to households/persons with calibrated confidence (entity resolution with gradient boosting and embeddings, representation learning, isotonic calibration, candidate blocking, champion/challenger pipelines), expanding addressable audiences beyond deterministic matching. - Audience Intelligence — advertising and marketing use cases: lookalike and predictive audiences (LAL across 1,000+ features), ML-driven smart audiences, layered retrieval + propensity, and incrementality/closed-loop optimization, with privacy-safe activation including data clean rooms. - ML-based Forecasting — audience growth, demand, and advertising yield/pricing forecasting that powers ad sales and marketing decisions. - Content Preferences & Affinity — genre-preference, content-preference, and single-title affinity modeling (two-tower retrieval with semantic content embeddings) that ranks audiences for upcoming titles and powers cross-channel promotion. What You’ll Bring Required - 5–8 years of industry experience in ML engineering or applied data science (3+ years with a Ph.D.). - Deep Python expertise and production-quality software engineering practices; production experience building and deploying ML at scale (millions+ of users/records). - Strong proficiency in Databricks (PySpark, Delta Lake, Workflows/DLT, MLflow, Unity Catalog) and solid SQL/Snowflake experience for feature sourcing and model-output delivery. - Experience with AWS ML services (SageMaker, S3, Lambda). - Strong understanding of ML model evaluation, A/B testing, and statistical inference; knowledge in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, causal/interpretable ML, forecasting, bandits, or optimization. - Demonstrated ability to lead technical decisions and mentor engineers. - Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent experience). - Excellent written and verbal communication, with the ability to advocate technical solutions to engineers, scientists, and product stakeholders. Preferred - Recommendation systems, personalization, identity resolution, or audience modeling in a media / streaming / ad-tech context. - Familiarity with Data Clean Room environments (Snowflake DCR, AWS Clean Rooms) and consent-aware activation. - Experience with two-tower / retrieval architectures, probabilistic identity resolution (graph-based matching, entity resolution), and probability calibration. - Hands-on experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, MCP), Databricks Genie Space configuration, and Snowflake Cortex. - Experience with feature stores (Databricks Feature Store, Tecton, Feast) and contributions to open source or ML publications. What We Offer: - A Great Place to work - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Machine Learning Engineer II ( Data & Audience Platform Team), Hyderabad About Warner Bros. Discovery Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet our Team Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role As a Machine Learning Engineer II, you will work alongside Senior and Staff engineers to build and maintain production ML pipelines, contribute to model development, and grow into a well-rounded ML engineer who bridges data science and software engineering. This is a hands-on role for someone with roughly 2–4 years of experience who is eager to work on high-impact ML systems at scale — from probabilistic identity graphs to single-title affinity models — and who wants to develop deep expertise across the full ML lifecycle. What You’ll Do ML Development & Modeling Build and maintain end-to-end ML pipelines for training, evaluation, and batch inference across use cases such as identity resolution, audience segmentation, and content affinity modeling. Implement and experiment with supervised, unsupervised, and ranking models in Python (scikit-learn, XGBoost/LightGBM, PyTorch). Engineer features from first-party viewership, engagement, subscription, and behavioral signals, guarding against data leakage, collinearity, and training/serving skew. Run structured offline experiments; evaluate with the right metrics (precision/recall, F1, AUC-ROC, calibration, lift) and document findings in MLflow. ML Infrastructure & Engineering Develop and maintain data and feature pipelines on Databricks (PySpark, Delta, Workflows) that feed the feature store and model-training workflows, with attention to idempotency and reproducibility. Write clean, tested, production-quality Python following engineering best practices (unit tests, code reviews, CI/CD). Use MLflow for experiment tracking, model registration, and versioning under the guidance of senior engineers. Support deployment and monitoring of batch inference jobs integrated with downstream activation platforms (e.g., Mosaic, FreeWheel, GAM) and data in Snowflake. Agentic AI & Modern Tooling Use AI-assisted development tools (Cursor, GitHub Copilot, Amazon Q) to accelerate coding, debugging, and documentation under guidance. Leverage Databricks Genie for natural-language exploration of governed Unity Catalog datasets — querying ML feature tables, model outputs, and audience segments. Use Snowflake Cortex (Copilot / Cortex Analyst) to accelerate data analysis and SQL authoring against audience and identity schemas. Learn and apply prompt-engineering patterns for LLM-assisted data exploration and feature generation, and participate in evaluating MCP (Model Context Protocol) tooling as the team expands agentic workflows. Collaboration & Growth Partner with Senior and Staff MLEs to understand system-design decisions and contribute meaningfully to technical discussions. Work cross-functionally with Data Engineering, Feature Engineering, and Analytics to ensure data quality and pipeline reliability. Document models, pipelines, and experiments clearly for team knowledge sharing. What You’ll Bring Required 2–4 years of industry experience in machine learning, data science, or ML engineering (or 1–2 years with a relevant M.S.). Strong Python proficiency; experience with pandas, NumPy, scikit-learn, and at least one deep-learning framework (PyTorch or TensorFlow). Hands-on experience with Spark/PySpark or equivalent large-scale data processing. Proficiency in SQL and familiarity with cloud data warehouses/lakehouses (Snowflake or Databricks). Experience with experiment-tracking tools (MLflow, Weights & Biases, or similar). Solid grasp of core ML concepts: classification, regression, ranking, embeddings, and model evaluation; plus strong CS fundamentals (data structures, algorithms, clean code). Bachelor’s degree in Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent practical experience). Ability to use AI tools to independently improve productivity across the ML lifecycle, and clear written and verbal communication. Preferred Experience with Databricks (notebooks, Delta Lake, Workflows/DLT, Unity Catalog, MLflow). Exposure to recommendation systems, audience segmentation, identity resolution, or forecasting. Familiarity with AWS services (SageMaker, S3, Lambda) and/or feature stores (Databricks Feature Store, Feast). Exposure to agentic AI tools: Cursor, GitHub Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, or MCP. What We Offer: - A Great Place to work - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role : As a Sr. Principal Data Scientist, you will operate at the highest technical individual-contributor level at Warner Bros. Discovery—serving as a company-wide authority in advanced Data Science, Machine Learning, and Applied AI. This role is designed for an elite practitioner with 15–18+ years of experience, including 10–14 years of deep, hands-on expertise in Data Science, ML, and AI systems at enterprise scale. Unlike leadership or management roles, this position is purely an IC role, focused on technical depth, architectural rigor, and scientific excellence, without formal people-management responsibilities. You will design, architect, and deliver some of WBD’s most complex and business-critical AI systems, directly influencing how the company creates, distributes, personalizes, monetizes, and optimizes content across streaming, linear TV, advertising, and direct-to-consumer platforms. This is a hands-on, high-impact role for a technologist who thrives on solving unsolved problems, pushing the boundaries of applied ML, and translating advanced science into durable business advantage. 1. Enterprise-Grade Applied AI & ML Leadership (IC) - Act as one of WBD’s  most senior technical ICs  in Data Science and Machine Learning. - Lead the  end-to-end design and implementation  of advanced ML systems across: - Content intelligence & metadata enrichment - Audience modelling & personalization - Forecasting, optimization, and experimentation - Advertising intelligence & monetization analytics - Set  technical direction and standards  for complex ML implementations without direct people management. 2. Advanced Modelling & Scientific Excellence - Design and implement  state-of-the-art models , including: - Large-scale recommender systems - Time-series forecasting & probabilistic models - Causal inference, experimentation & uplift modelling - NLP, generative AI & multimodal ML systems - Computer vision & video intelligence pipelines - Apply rigorous statistical thinking, experimentation discipline, and scientific validation to all solutions. - Serve as a  final technical reviewer  for high-risk or high-impact ML solutions. 3. Architecture of Scalable ML Systems - Architect  production-grade ML systems  integrated with WBD’s cloud data ecosystem (AWS, Snowflake, GCP). - Define best practices for: - Feature engineering & feature stores - Model lifecycle management & MLOps - CI/CD for ML, model monitoring, and drift detection - Reproducibility, governance, and responsible AI - Partner deeply with data engineering, platform, and product engineering teams to ensure scalable, resilient delivery. 4. High-Impact Business Problem Solving - Own and deliver  mission-critical AI solutions  across: - Content performance prediction & ratings intelligence - Marketing attribution & lifecycle analytics - Search, discovery & ranking systems - Ad load optimization & pricing intelligence - Operational forecasting & automation - Translate complex modelling outputs into  clear, executive-ready insights  that drive decisions. 5. Executive & Cross-Functional Influence (Without Line Management) - Serve as a  trusted technical advisor  to senior leaders across Streaming, Content, Ad Sales, Marketing, and Technology. - Communicate complex ML concepts with clarity and credibility to non-technical stakeholders. - Influence enterprise AI roadmaps, architectural decisions, and investment priorities through expertise—not hierarchy. 6. Technical Mentorship & Community Leadership - Mentor senior and staff-level data scientists through  technical guidance, design reviews, and deep problem-solving . - Contribute to internal AI communities of practice, technical forums, and standards bodies. - Elevate overall engineering and scientific rigor across the Data Science organization. Qualifications & Experiences: - Master’s or Ph.D.  in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, Operations Research, or related disciplines. - 18–20 years  of total experience, with  13–15 years  in Data Science/ML, including hands-on technical leadership. - Deep expertise in: - Predictive modeling, optimization, and advanced ML techniques - MLOps and large-scale model deployment - Modern cloud ecosystems (AWS/GCP/Snowflake) - Python, PyTorch, TensorFlow, SQL, ML frameworks - Experiment design, causal inference, and statistical modeling - Demonstrated experience in Media & Entertainment, streaming, digital advertising, or consumer intelligence. - Strong track record of delivering enterprise-impact through AI solutions. - Exceptional communication skills, including the ability to influence executives and inspire technical teams. Preferred - Experience developing or customizing Large Language Models or multimodal foundation models. - Patent, publication, or conference-track record in ML/AI. - Experience with video intelligence, CV for media workflows, or content metadata systems. - Experience partnering with product and engineering organizations in a fast-paced environment. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Staff MLE,   Search &   Personalization, Content Discovery Location: Seattle, San Francisco Bay Area, New York About You: We’re   looking for a   Staff Machine Learning Engineer   to lead the design and evolution of   ML and AI driven   Search   algorithms   for   our global streaming app,   HBO   Max . This role will own the end-to-end search   algorithm innovation   from retrieval and ranking to personalization and experimentation ,   impacting   how millions of users discover content globally. You will   operate   at the intersection of ML, systems, and   product , bringing both   deep   expertise   in search/relevance systems   and   strong technical leadership .   You’ll   help define the roadmap, drive architecture decisions, and elevate the team’s ability to build and iterate on high-quality search experiences. Responsibilities: - Lead the design and development of   large-scale   model driven   search   algorithms   including retrieval, ranking, and query understanding - Define and evolve the   technical strategy for search , balancing relevance, latency, and scalability - Drive end-to-end ML systems: data pipelines, feature engineering, model training, experimentation, and serving - Partner closely with product, data, and infrastructure teams to shape   and execute on   the   search roadmap and user experience - Mentor engineers   and data scientists   and raise the bar on   algorithm development,   system design,   ML   and   engineering practices - Identify   and drive high-impact opportunities across search and personalization - Motivate,   inspire   and create a culture of experimentation and data-driven innovation while constantly striving to be an advocate for doing what is right for our customers Requirements: - 8+ years of industry experience, with 4+ years as tech lead experience (preferred) - Deep   expertise   in   search and/or ranking   algorithms ( e.g., retrieval, LTR, semantic search ,   query understanding , entity recognition ) - Strong experience building   large-scale ML systems in production - Proven ability to   lead technical direction and influence across teams - Experience with   online experimentation and metrics-driven development - Strong programming skills in Python ( Java/Go a plus ) - Experience with distributed systems and cloud platforms (AWS/GCP/Azure) - Solid understanding of data fundamentals (SQL, pipelines, feature stores) - Excellent communication skills and ability to work cross-functionally Nice to Have - Experience with recommender systems or personalization - Experience with NLP techniques - Familiarity with vector search / ANN ( Faiss ,   ScaNN , etc.) - Experience in streaming, marketplace, or content discovery platforms How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $192,570.00 - $357,630.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. If you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. At HBO Max, storytelling takes center stage. We’re one of the world’s most iconic entertainment brands — home to bold originals and unforgettable characters. While audiences binge award-winning content, breaking news, and sports around the clock, our teams stay busy at work creating what’s next in streaming. From Succession, Euphoria, and The Sopranos to global franchises like Game of Thrones and Harry Potter, our content sparks conversation and shapes culture. HBO Max delivers boundary-pushing stories across genres and platforms, connecting millions of viewers across 90 countries globally— and we’re just getting started. We're home to the most talked about shows and movies, granting audiences access to the worlds of HBO, Harry Potter, DC, Warner Bros., ID, Adult Swim, A24, and more. Turn your streaming obsession into a career— we’re hiring! About You: We are looking for a   passionate   Staff Machine Learning Engineer to bridge the gap between   cutting-edge   ML   algorithm development   and production grade, scalable softwa re engineering for our search and personalization systems. In this role, you will be the   technical   leader   of our engineering rigor,   design the core architecture,   establish   engineer ing   best   practices, creat e   scalable   MLOps   pipelines, and design a codebase that allows the team to iterate, deploy, and quickly experiment in production. You will act as a force multiplier, elevating the software engineering capabilities of the entire ML team. Responsibilities: - Recommendation & Search   model training   a rchitecture:   Architect, build, and scale recommendation systems   powering   personalization and search experiences across our streaming platforms. - Codebase Architecture :   Design modular, scalable ML repositories built for rapid iteration, fast deployment, and production experimentation. - Engineering Excellence :   Establish   coding standards, testing frameworks, code review workflows, and CI/CD pipelines using open-source cloud technologies   for ML and DS workstreams . - Production Velocity :   Build infrastructure abstractions and components that allow seamless transition from model training to large-scale serving. - Cross-Functional Delivery:   Collaborate with   other ML engineers ,   data scientists and   product managers,   to drive complex ML projects from conception to completion. - Strategic Planning :   Partner with   product and   engineering leadership to define, plan, and deliver against long-term strategic goals. - Culture & Mentorship:   Mentor and influence engineers across organizations by   demonstrating   high-quality work, advocating for the customer, and fostering an innovative,   engineering -driven culture. Requirements: - 8+ years of industry experience, with 4+ years as tech lead experience (preferred) - D eep   practical   knowledge in designing   scalable, production-grade Search or Recommendation systems architecture - Knowledge of large-scale distributed   systems, architecture, APIs, and   databases. - Solid   practical   understanding   in modern machine learning lifecycle , common pain-points, and research and production environments . - Staff level experience building production systems with   expertise   in   Python/Java ,   containerization , and cloud platforms. - Hands-on experience with   MLOps   tools and frameworks ( MLflow ,   Kubeflow,   Sagemaker ,   etc ) , or   building internal systems. - Familiarity with m achine learning algorithms ( in particular for   recommender systems) is   a strong   plus How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $187,670.00 - $348,530.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. If you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN. To see what it’s like to work at CNN, follow @WBDLife on  Instagram  and  X ! We are CNN. THE WORLD'S MOST ESSENTIAL AND ENGAGING SOURCE OF DIGITAL NEWS. We are in the midst of rapid transformation and need our next generation of innovators, makers, and dreamers who will lead and drive our growth. We aim to make the world a better, more connected place. Your New Role… CNN is seeking a Specialist, AI Innovation to support and drive the day-to-day execution of AI work across the newsroom. This position plays a key role in operationalizing projects and turning ideas into real tools, workflows and editorial use cases that improve how journalists work.  You will help initiate, manage and move forward a growing portfolio of AI projects, while also working closely with reporters, producers and editors to understand how AI can support their day-to-day work. The role requires strong organizational skills, editorial judgment and a practical understanding of how AI tools can be applied in a newsroom setting while maintaining the highest editorial standards. The ideal candidate is organized, collaborative and ambitious—someone who can keep complex projects and workstreams on track while contributing their own ideas and identifying opportunities for AI to make a meaningful impact. Your Role Accountabilities… - Manage timelines, priorities and deliverables across a portfolio of AI Innovation projects, ensuring consistent progress across broad, cross-functional teams - Support intake and prioritization of new ideas and requests from across the newsroom, helping focus efforts on the highest-impact opportunities - Work closely with reporters, producers and editors to understand workflows and identify practical opportunities for AI to improve day-to-day work - Uphold CNN’s standards of accuracy, fairness and transparency across AI-powered tools and AI-generated output - Partner with teams across editorial, product, engineering, legal, and business to keep projects aligned and moving forward - Champion adoption of AI tools and workflows, including trainings, onboarding and ongoing journalist support Qualifications & Experience… - 2+ years of experience in a newsroom, digital media organization, or cross-functional role supporting editorial teams - Strong organizational and project management skills, with the ability to manage multiple workflows, prioritize effectively, and deliver against deadlines in a fast-paced newsroom environment - Strong understanding of newsroom workflows, including reporting, editing, and video production - Hands-on experience applying AI tools to editorial or product workflows, including prompt development, testing, and evaluating outputs for accuracy and quality - Experience working with project management systems, data and analytics to assess performance, identify trends, and inform decisions - Experience collaborating with product and engineering teams on tool development, integrations, or workflow improvements - Strong communication skills, with the ability to work effectively across teams and align stakeholders How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $70,000.00 - $130,000.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Staff Product Manager, Technical (PM-T) – Content Intelligence About Warner Bros. Discovery: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet Our Team: When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons. and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Roles and Responsibilities : The Content Intelligence team is seeking a Staff-level Technical Product Manager (PM-T) to support the development and execution of AI/ML capabilities powering next-generation content localization workflows. This role focuses on context-aware localization, including transcription, subtitling, translation, captioning, audio description and dubbing workflows, as well as content intelligence capabilities that improve localization quality through scene, character, dialogue, and metadata awareness. These capabilities play a critical role in expanding the global reach, accessibility, and discoverability of WBD content by enabling content availability across more languages, markets, and audience segments. This is a hands-on product management role with a strong emphasis on execution, cross-functional coordination, and operationalizing AI/ML capabilities within content localization workflows. The ideal candidate is detail-oriented, comfortable working closely with engineering and program management, and experienced in defining requirements and driving delivery for AI/ML-powered systems and backend platforms. Key Responsibilities - Partner with engineering and program managers to drive execution across sprint cycles, including backlog management, story writing, feature clarification, dependency management, and release planning. - Write product requirement documents (PRDs) and define detailed functional and technical specifications for AI-powered localization workflows, including translation, dubbing, captioning, subtitle generation, audio description, editorial review, quality evaluation, and workflow orchestration systems. - Define and support capabilities that leverage content context, including character identity, dialogue history, scene metadata, terminology, style guides, content metadata, and franchise-specific knowledge to improve localization quality and consistency. - Support the evolution of localization workflows from asset-level processing to context-aware systems that leverage metadata, character relationships, dialogue history, content intelligence, and editorial feedback to improve quality and consistency at scale. - Collaborate with AI/ML teams to operationalize context-aware localization systems utilizing large language models (LLMs), metadata enrichment, retrieval-based approaches, and multimodal content understanding. - Facilitate near-term roadmap planning and coordination across engineering and partner teams supporting localization and content intelligence initiatives. - Drive cross-functional alignment and decision-making across AI/ML engineering, media supply chain, global content operations, human-in-the-loop (HITL) operations, editorial, legal, accessibility, and external vendor partners to remove blockers, manage dependencies, and ensure successful execution of localization programs. - Partner with Product Data Science to define and evaluate experimentation frameworks, interpret results, and assess localization quality, model performance, post-edit efficiency, workflow productivity, and business impact to inform product decisions and prioritization. - Work with engineering and system architects to define integration requirements across localization supply chain systems, order management platforms, editorial tools, content management systems, metadata services, and adjacent AI/ML platforms. - Assist in evaluating the impact of feature changes across adjacent systems on localization workflows and AI/ML pipelines, working with partner teams to scope dependencies and downstream effects. - Collaborate with stakeholders across content operations, localization teams, marketing, and cross-functional technology teams to gather requirements and incorporate feedback while effectively managing the uncertainty inherent in AI/ML development. - Partner with editorial and localization operations teams to design and optimize human-in-the-loop workflows, ensuring reviewer feedback mechanisms align with model evaluation, quality measurement, and continuous improvement objectives. - Directly support product operations, including triaging user feedback, investigating product issues, and partnering with engineering and program management to prioritize fixes and enhancements. What to Bring : - 9–12 years of product management experience, including experience as a Technical Product Manager. - Strong experience writing PRDs, defining features, and partnering with engineering teams through agile development and sprint execution processes. - Familiarity with machine learning systems, including deep learning and large language models, deployed in production environments. - Experience working with AI/ML systems on cloud platforms such as AWS or GCP, particularly those involving human-in-the-loop workflows, content processing pipelines, or post-editing workflows. - Strong attention to detail, with the ability to manage multiple concurrent feature tracks, dependencies, and decisions across complex systems. - Experience translating business and operational requirements into technical product capabilities and measurable outcomes. Preferred Qualifications: - Background in Computer Science, Engineering, Data Science, or a related technical field. - Familiarity with language AI technologies and media localization workflows, including Automatic Speech Recognition (ASR), Machine Translation (MT), Large Language Models (LLMs), Text-to-Speech (TTS), dubbing, captioning, subtitling, and audio description. - Experience with context-aware localization systems leveraging metadata, terminology management, style guides, character context, dialogue history, and retrieval-based approaches. - Familiarity with localization quality evaluation methodologies, human-in-the-loop review processes, and post-editing workflows. - Comfortable working with AI evaluation methodologies and quality metrics, including precision, recall, confidence scoring, translation quality assessment, and human evaluation frameworks. What Success Looks Like: - Deliver scalable AI-powered localization capabilities that improve localization quality, editorial efficiency, accessibility outcomes, and operational throughput. - Advance context-aware localization workflows by incorporating content metadata, character context, dialogue history, and editorial feedback into AI-assisted processes. - Drive measurable improvements in localization quality, post-edit effort, consistency, accessibility coverage, and cost efficiency across global content catalogs. - Successfully coordinate delivery across engineering, AI/ML, editorial, operations, legal, accessibility, and vendor teams while maintaining strong execution rigor and stakeholder alignment. - Help scale the organization's localization AI capabilities by translating emerging AI technologies into operationally viable products that deliver measurable business value What We Offer: - A Great Place to work. - Challenging ML problems in Media Domain. - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. At HBO Max, storytelling takes center stage. We’re one of the world’s most iconic entertainment brands — home to bold originals and unforgettable characters. While audiences binge award-winning content, breaking news, and sports around the clock, our teams stay busy at work creating what’s next in streaming. From Succession, Euphoria, and The Sopranos to global franchises like Game of Thrones and Harry Potter, our content sparks conversation and shapes culture. HBO Max delivers boundary-pushing stories across genres and platforms, connecting millions of viewers across 90 countries globally— and we’re just getting started. We're home to the most talked about shows and movies, granting audiences access to the worlds of HBO, Harry Potter, DC, Warner Bros., ID, Adult Swim, A24, and more. Turn your streaming obsession into a career— we’re hiring! Manager, Machine Learning Engineering – Video AI & Studio AI Job Description What We Do We build next-generation AI systems for video, spanning both large-scale video understanding and creative studio workflows. Our work combines computer vision, multimodal learning, and machine learning to enable capabilities such as scene understanding, metadata generation, visual effects, storyboarding, and color enhancement across media content. We focus on taking ML from research to production, integrating models into real-world systems used by engineering, product, and creative teams. Our goal is to build scalable, high-quality solutions that power both content intelligence and creative workflows. What You’ll Do - Lead a team of machine learning engineers working on video AI across understanding and creative applications - Stay hands-on, contributing directly to modeling, prototyping, and production systems - Drive execution across the full ML lifecycle: problem definition, modeling, evaluation, and deployment - Partner with product, creative, and engineering teams to define priorities and deliver impactful ML-powered features - Build and scale production-grade ML systems for video understanding and creative workflows - Balance rapid iteration with building robust, scalable systems - Provide technical leadership and mentorship, raising the bar for ML and engineering practices - Collaborate with platform and infrastructure teams to ensure reliable and scalable solutions Qualifications & Experience - 8+ years of experience in machine learning / software engineering, with a focus on computer vision, video understanding, and gen AI - 2+ years of experience leading or mentoring engineers, with a strong preference for hands-on leadership - Strong experience with deep learning frameworks (e.g., PyTorch, TensorFlow) - Proven track record of building and deploying end-to-end ML systems in production - Strong background in computer vision, video understanding, or multimodal systems - Experience with large-scale datasets and distributed systems - Experience with generative AI techniques (e.g., diffusion, image/video generation) - Strong system design and architecture skills - Ability to operate in ambiguous, fast-moving environments while maintaining execution focus - Strong collaboration and communication skills across technical, product, and creative teams How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $187,670.00 - $348,530.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. If you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Senior Manager, Machine Learning Engineering (Data & Audience Platform), Hyderabad About Warner Bros. Discovery Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com. Meet Our Team Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks , with strong working knowledge of Snowflake and AWS , and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role This is the most critical hire for WBD’s Hyderabad ML Engineering build-out. As Senior ML Engineering Manager, you will establish, lead, and grow the Hyderabad ML Engineering center of excellence — a team of seven individual contributors spanning identity intelligence, audience intelligence, content affinity modeling, forecasting, and ML platform engineering. You will be the single accountable leader for the team’s technical execution, people development, and cross-functional delivery in India, operating as a true extension of the Director of Engineering. All of the Hyderabad ML/DS individual contributors report to you, and you report into the Director. This role demands an exceptional blend of technical depth (you must credibly engage in Staff-level ML architecture discussions), people leadership (you will manage a diverse IC ladder from MLE 2 to Staff), and organizational influence (you will represent Hyderabad across WBD’s global data, product, and advertising organizations). You are not just a manager — you are a builder, a technical partner, and a culture carrier. Roles & Responsibilities: Team Leadership & People Development - Directly manage 7 ICs (2× MLE 2, 3× Senior MLE, 1× Staff MLE, 1× Staff DS); own their performance, growth, and career development. - Establish a high-performance engineering culture: technical excellence, ownership, psychological safety, rigorous experimentation, and continuous learning. - Define clear role expectations, growth paths, and promotion criteria aligned with WBD’s global ML engineering job family; conduct regular 1:1s, performance reviews, and career conversations, addressing performance gaps proactively. - Lead hiring for the Hyderabad team: define the hiring bar, design interview processes, attract top ML talent, and build a strong, diverse local pipeline. - Foster an inclusive, collaborative environment that bridges India and US time zones effectively. Technical Leadership & Oversight - Maintain sufficient technical depth to review ML architecture proposals, challenge design decisions, and unblock technical escalations across all workstreams. - Partner with the Staff MLE to set and enforce technical standards: MLOps practices, code quality, model-evaluation rigor, and documentation. - Own the technical roadmap for the team’s ML systems — identity intelligence, audience intelligence, content affinity, forecasting — in alignment with global ML strategy. - Drive adoption of the team’s core stack: Databricks (primary), AWS SageMaker, Snowflake, MLflow, and agentic AI tooling (Cursor, Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, MCP). - Ensure production ML systems are reliable, monitored, cost-efficient, and continuously improved; own the team’s on-call and incident-response posture. Program Execution & Delivery - Own end-to-end delivery accountability for Hyderabad’s ML projects: scope, milestones, dependencies, risks, and stakeholder communication. - Run effective agile processes adapted to ML realities (research uncertainty, data dependencies, experiment iteration), with D90 planning rhythms and quarterly OKR alignment. - Proactively identify and resolve cross-team dependencies with Data Engineering, Product, Ad Sales, and Legal/Privacy. - Maintain a clear view of capacity, prioritization trade-offs, and commitments; communicate status and risks transparently to the Director. Key ML Workstream Ownership - Identity Intelligence: oversee delivery of the probabilistic ID spine — resolving unauthenticated signals (device IDs, 1P cookies) to households/persons with calibrated confidence across all WBD brands. - Audience Intelligence: oversee ML Promo Optimizer, STAT v2 (single-title affinity retrieval), lookalike modeling (LAL 2.0+ in Snowflake DCR), and segmentation that power advertising and marketing activation. - Content Affinity & Personalization: oversee genre-preference and content-affinity models and engagement-based personalization signals feeding HBO Max and CNN surfaces. - Forecasting: oversee ML-based audience, engagement, and yield/revenue forecasting supporting Finance, Content, and Marketing planning. - MLOps Platform: ensure the team’s feature store, training/serving pipelines, model registry, and monitoring are production-grade, well-documented, and consistently adopted. Cross-functional & Organizational Leadership - Serve as the primary point of contact for the Hyderabad ML team across Product, Marketing, Ad Sales, Data Engineering, Legal/Privacy, and Finance. - Build strong relationships with US-based ML leadership, Data Science, and Platform Engineering counterparts so Hyderabad is a fully integrated — not siloed — part of the global ML organization. - Partner with the Director on long-range team strategy, capability planning, and organizational design; represent WBD ML externally where appropriate (talent branding, university partnerships). - Ensure ML systems meet privacy, governance, and compliance requirements. Agentic AI & Innovation Culture - Champion agentic AI development: establish norms for using Cursor, GitHub Copilot, Amazon Q, and MCP-based tooling to accelerate ML velocity, with measurable improvements in quality and lifecycle efficiency. - Drive strategic adoption of Databricks Genie (governed, self-service NL interfaces over Unity Catalog) and Snowflake Cortex (Copilot/Analyst, Cortex Search, and selective Fine-Tuning) so ML outputs are accessible to non-technical stakeholders. - Create space for innovation: structured prototyping time, internal tech talks, and contribution to WBD’s broader ML community of practice; bring relevant external insights into the roadmap. What You’ll Bring - 12+ years of total experience in ML, data science, or ML engineering, including 3–5+ years in engineering management. - Demonstrated success leading and growing teams of ~6–12 ML engineers and/or data scientists, including a multi-level IC ladder (junior through Staff). - Strong technical foundation in ML: you can read and critique model-architecture proposals, review ML code, and engage credibly in Staff-level discussions — you have personally built and shipped production ML. - Hands-on (current or recent) experience with the ML stack: Python, Databricks/Spark, MLflow, cloud ML (AWS SageMaker preferred), and SQL/Snowflake. - Proven track record delivering complex, multi-month ML projects in production at scale. - Experience in a matrixed, global organization with cross-timezone collaboration. - Excellent communication: translating technical complexity for executive and non-technical audiences, and business context for engineers. - Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field. Preferred - ML leadership in streaming, media, ad-tech, or consumer internet — particularly audience modeling, identity resolution, personalization, or recommendations. - Familiarity with WBD’s ecosystem: Databricks, Snowflake, AWS, FreeWheel/GAM, or equivalent ad-tech activation stacks. - Experience managing teams across India and US time zones, and building ML teams from early stages (hiring bar, onboarding playbooks, culture). - Familiarity with Databricks Genie, Snowflake Cortex, MCP, and modern AI-assisted development workflows. - Experience with Data Clean Rooms and privacy-preserving ML. What We Offer: - A Great Place to work - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. As Sr. Staff – Data Science & Applied AI (Cloud AI), you will be a core technical contributor within WBD’s AI Center of Excellence (CoE). This role is designed for a hands-on senior architect who operates at the intersection of enterprise architecture, applied AI, Generative AI, agentic AI, and cloud platform engineering. You will translate complex business challenges into scalable AI solution architectures, production-ready platforms, and reusable technical patterns that drive measurable enterprise value. You will serve as a senior individual contributor, partnering closely with Product, Engineering, Data, Security, and Business stakeholders to design, govern, and scale modern AI solutions across the organization. The role combines solution architecture leadership with deep expertise in GenAI application design, agentic systems, and AI cloud architecture on AWS and Snowflake. Enterprise AI Solution Architecture - Define end-to-end solution architecture for enterprise AI, GenAI, and agentic AI applications aligned to business and technology strategy. - Translate business workflows and operational challenges into scalable AI solution patterns, including autonomous and semi-autonomous agent use cases. - Partner with product, engineering, data, and business teams to move AI and GenAI use cases from concept and pilot into production at enterprise scale. - Create reusable architecture patterns, accelerators, reference implementations, and technical standards to speed AI adoption across teams. AI Cloud & Platform Architecture - Design and govern the cloud architecture for AI/ML/GenAI platforms across AWS and Snowflake. - Define scalable patterns for compute, storage, networking, identity, security, environment setup, and enterprise integration across development, test, and production environments. - Build architecture patterns for MLOps and LLMOps covering deployment, experimentation, model lifecycle management, monitoring, retraining, and version control. - Ensure platform reliability, resilience, observability, compliance, and cost optimization for AI solutions in production. - Establish architecture standards and reference frameworks that accelerate AI solution delivery across business domains. Productionization, Engineering & Governance - Collaborate with Data Engineering, Platform Engineering, DevOps, and Security teams to productionize AI and GenAI solutions in scalable cloud environments. - Design CI/CD and automation patterns for model deployment, prompt/version management, testing, release control, and operational support. - Implement monitoring for model drift, prompt drift, performance degradation, usage patterns, system health, and data integrity. - Support governance, risk management, and responsible AI initiatives by embedding security, privacy, compliance, and auditability into solution design. - Innovation & Technical Leadership - Stay current with advancements in foundation models, multimodal AI, agent frameworks, orchestration patterns, and cloud-native AI services. - Provide architecture guidance, design reviews, and technical mentorship across cross-functional teams. - Contribute to enterprise-wide AI best practices, reusable frameworks, and technical decision-making to elevate the maturity of the AI ecosystem. Qualifications & Experiences: - Bachelor’s degree, Master’s degree, or higher in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline. - 8+ years of relevant experience in solution architecture, data science, machine learning, or AI engineering, with at least 2+ years of experience in Generative AI / LLM-based solutions. - Demonstrated track record of designing and delivering production-grade AI/ML/GenAI solutions with measurable business impact. - Strong experience in architecting enterprise AI solutions across business workflows, data ecosystems, and cloud platforms. - Hands-on expertise in building and scaling GenAI and LLM applications, including prompt engineering, RAG architectures, semantic search, embeddings, and evaluation frameworks. - Experience designing or supporting agentic AI systems, including orchestration, tool usage, memory, guardrails, and human oversight patterns. - Deep understanding of cloud-native AI/ML architecture principles, including deployment patterns, platform reliability, observability, security, and cost optimization. - Experience establishing reusable architecture patterns, technical standards, and governance controls for AI systems in enterprise environments. - Strong collaboration skills with Product, Engineering, Data, Security, and Business teams in global, cross-functional settings. Key Technical Skills & Expertise - Hands-on experience supporting Generative AI and ML workloads on enterprise cloud platforms, including AWS and Snowflake - Strong working knowledge of LLM-based systems, including model hosting, inference optimization, and integration into cloud-native architectures. - Experience enabling RAG pipelines and GenAI applications through secure data access patterns, vector search, and enterprise data integration. - Familiarity with embedding models, semantic search, and vector storage technologies, including OpenSearch vectors and Snowflake Cortex Search. - Understanding of LLM evaluation considerations within platform architecture, including performance monitoring, cost optimization, and quality metrics. - Experience designing MLOps and LLMOps architectures for model deployment, monitoring, retraining, and lifecycle governance. - Strong expertise in AWS cloud architecture, including VPC, IAM, S3, ECS/EKS, SageMaker, Bedrock, and observability tooling. - Hands-on experience with infrastructure as code, CI/CD pipelines, and containerized AI workloads (Docker, Kubernetes). - Working knowledge of Snowflake architecture, including Snowpark, Snowpipe, Streams & Tasks, and Cortex AI. - Deep understanding of Responsible AI, data security, privacy controls, and governance requirements for enterprise AI platforms. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Senior Staff Product Manager – Technical (Data & Audience Platform Team), Hyderabad About Warner Bros. Discovery: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet our team The Data and Audience Platform team sits within the Data & Analytics organization in WBD's Global Tech division. We build the data platform behind our streaming services and content businesses - the pipelines, data lakes, and serving infrastructure that turn billions of events into audience insights, personalization, and intelligent products. About the Role The Senior Staff Product Manager-Tech, AI/ML Roadmap and Platform Strategy, will define and drive the Data & Audience Platform (DAP) AI roadmap across predictive ML, GenAI, agentic workflows, AI-enabled analytics, data activation, and AI-native platform capabilities. This role is intentionally AI-centric: it exists to elevate DAP from a data and analytics platform organization into a product-led AI enablement function that identifies the highest-value AI opportunities, chooses the right technologies, and converts experimentation into durable business outcomes. This role will be accountable for disciplined AI product strategy: selecting the right problems, validating that the newest technology is actually the best fit, defining measurable business value up front, and ensuring platform investments are reusable, governed, cost-aware, and scalable. The role will work across DAP, engineering, analytics, data science, architecture, product, operations, privacy/legal, AI governance, and senior leadership to make AI investments actionable, safe, and outcome driven. Roles & Responsibilities: - Shape AI product strategy and roadmap priorities across DAP platform areas. - Evaluate AI/ML opportunities through value, feasibility, cost, data readiness, governance, and reuse lenses. - Write AI-focused PRDs, product briefs, model/agent behavior requirements, evaluation criteria, and launch readiness requirements. - Partner with engineering, data science, and architecture to compare model, platform, vendor, and implementation tradeoffs. - Define KPIs and decision frameworks that connect AI outputs to business outcomes. - Run AI roadmap, prioritization, value review, and post-launch measurement forums. - Translate complex AI/ML concepts into clear executive narratives and actionable decisions. - Identify when AI work should be standardized as a shared platform capability versus delivered as a bespoke solution. - Work with cross-functional teams to intake, define, identify risks, and schedule work to develop key features. - Formulate a point of view on how proposed features align with business goals and our tech strategy. What to Bring: - 12+ years of product management, technical product management, AI/ML product strategy, data platform, analytics, or related experience. - Deep experience defining and delivering AI/ML, GenAI, data platform, customer intelligence, analytics, activation, or enterprise platform products at scale. - Strong working knowledge of AI/ML product concepts including model lifecycle, experimentation, model evaluation, MLOps, data quality, governance, semantic layers, feature/data products, and post-launch performance measurement. - Practical fluency in modern AI patterns such as LLMs, RAG, agentic systems, AI orchestration, prompt and agent lifecycle management, human-in-the-loop workflows, and AI observability. - Demonstrated ability to set product vision and direction across multiple teams and highly ambiguous technical domains. - Strong ability to evaluate technology tradeoffs across capability, quality, scalability, privacy, security, cost, maintainability, and business value. - Excellent executive communication skills with the ability to translate technical AI concepts into clear decisions, narratives, and value cases. - Proven ability to influence without authority across engineering, architecture, data science, TPM, analytics, operations, business, governance, and senior leadership teams. - Track record of delivering measurable customer, business, operational, or platform impact from technical product investments. The Nice to Haves - Experience with streaming media, digital video, Customer 360, personalization, recommendations, content intelligence, advertising analytics, audience activation, commerce analytics, marketing analytics, or global platform products. - Experience with AI governance, responsible AI, model risk review, privacy/security requirements, or compliance needs for AI-powered products. - Experience creating scalable intake, prioritization, value management, and post-launch measurement mechanisms for AI portfolios. - Experience with AI cost management, cloud/data platform FinOps, model inference cost tradeoffs, vendor evaluation, or build/buy/reuse decisioning. - Experience mentoring senior PMs / PM-Ts and raising product craft across a matrixed organization. What We Offer: - A Great Place to work. - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. At HBO Max, storytelling takes center stage. We’re one of the world’s most iconic entertainment brands — home to bold originals and unforgettable characters. While audiences binge award-winning content, breaking news, and sports around the clock, our teams stay busy at work creating what’s next in streaming. From Succession, Euphoria, and The Sopranos to global franchises like Game of Thrones and Harry Potter, our content sparks conversation and shapes culture. HBO Max delivers boundary-pushing stories across genres and platforms, connecting millions of viewers across 90 countries globally— and we’re just getting started. We're home to the most talked about shows and movies, granting audiences access to the worlds of HBO, Harry Potter, DC, Warner Bros., ID, Adult Swim, A24, and more. Turn your streaming obsession into a career— we’re hiring! Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) — ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, Machine Learning Engineering does rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks, with strong working knowledge of Snowflake and AWS, and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role: This is a senior, high-ownership US-based role that sits between our Senior MLE and Staff MLE levels. You will own the design and delivery of production ML systems end to end and take on cross-cutting technical leadership: setting patterns, driving key architectural decisions on flagship workstreams, and raising the bar for the broader ML organization — including close partnership with our Hyderabad ML team. As a US-based senior engineer, you will also serve as a technical anchor and time-zone bridge across the global team: framing ambiguous problems, unblocking others, and translating business priorities from US-based Product, Marketing, and Ad Sales stakeholders into an executable ML roadmap. This role is ideal for engineers with roughly 5–8 years of experience (3+ with a PhD) who operate with strong autonomy, lead by influence, and can move fluidly from hands-on modeling and pipeline engineering to architecture and mentorship. You will do meaningful individual technical work while beginning to exercise Staff-level scope across initiatives. What You’ll Do: ML System Design & Technical Leadership Lead end-to-end development of production ML systems: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring. Own one or more flagship ML products — e.g., probabilistic identity resolution (matching unauthenticated device IDs and 1P cookies to households/persons with calibrated confidence), single-title affinity (two- tower retrieval), lookalike modeling, or forecasting — and drive their technical direction. Make and document key architectural decisions across a workstream (feature-store design, training/serving patterns, evaluation frameworks); provide deep trade-off analysis on scalability, latency, reliability, and cost. Design scalable feature and inference pipelines on Databricks (PySpark, Delta, Workflows/DLT, Unity Catalog) integrated with Snowflake and activation systems (Mosaic, FreeWheel, GAM), with documented feature contracts, backfill paths, and freshness SLAs. Establish and evangelize patterns that other engineers adopt; anticipate risks and failure modes before they surface. Modeling & Experimentation Develop and optimize models across the ML spectrum: gradient boosting (XGBoost/LightGBM), embedding/two-tower retrieval, neural ranking, probability calibration (e.g., isotonic regression), and probabilistic/graph- based matching. Design rigorous offline and online experiments; define evaluation frameworks (precision/recall, AUC-ROC, NDCG, decile lift, calibration curves) appropriate to each use case. Apply causal-inference techniques (propensity scoring, uplift/incrementality modeling) to measure true lift of audience targeting on engagement and retention KPIs. Contribute to lookalike modeling (LAL 2.0+) using 1,000+ first- and third- party features, including privacy-safe builds inside Data Clean Rooms (Snowflake DCR). MLOps & Infrastructure Champion MLOps best practices: model versioning, champion/challenger promotion, automated retraining triggers, drift detection, and production monitoring with MLflow on Databricks. Build and maintain robust, reproducible, auditable ML pipelines on Databricks (and AWS SageMaker where appropriate, e.g., the identity- resolution track); enforce leakage prevention and training/serving consistency. Shape the team’s feature-store strategy — feature contracts, backfills, and freshness SLAs — and implement data-quality checks, model-health dashboards, and alerting thresholds. Embed FinOps cost discipline (compute caps, auto-termination, job tagging) into pipeline design. Agentic AI & Modern Development Actively use and advocate for AI-assisted development: Cursor, GitHub Copilot, and Amazon Q for code generation, review, and documentation. Leverage Databricks Genie as a governed natural-language analytics layer — configuring Genie Spaces over ML feature tables and audience datasets to enable self-service exploration for cross-functional stakeholders. Use Snowflake Cortex (Copilot, Cortex Analyst, Cortex Search) to accelerate SQL authoring, data discovery, and RAG-based internal tooling over Snowflake-resident identity and audience data. Design and prototype agentic ML workflows (MCP-compatible tooling, LangChain/LangGraph) to automate repetitive tasks such as data validation, feature selection, and hyperparameter search; evaluate LLM- based approaches for metadata enrichment and content understanding. Mentorship & Cross-functional Collaboration Mentor Senior and MLE 2 engineers — including members of the Hyderabad team — through code reviews, design discussions, and pairing; contribute to and help set team technical standards. Serve as a US-based point of contact and time-zone bridge for the global ML team; help align priorities and unblock the India team across time zones. Partner with US-based Product, Marketing, and Ad Sales stakeholders to translate business requirements into ML problem formulations, and with Data Engineering on data contracts and pipeline SLAs. Communicate model performance, trade-offs, and business impact clearly to technical and non-technical stakeholders. Flagship Projects You’ll Work On Identity Intelligence — foundational, privacy-safe identity across all WBD brands: probabilistic ID resolution that resolves unauthenticated signals to households/persons with calibrated confidence (entity resolution with gradient boosting and embeddings, representation learning, isotonic calibration, candidate blocking, champion/challenger pipelines), expanding addressable audiences beyond deterministic matching. Audience Intelligence — advertising and marketing use cases: lookalike and predictive audiences (LAL across 1,000+ features), ML-driven smart audiences, layered retrieval + propensity, and incrementality/closed-loop optimization, with privacy-safe activation including data clean rooms. ML-based Forecasting — audience growth, demand, and advertising yield/pricing forecasting that powers ad sales and marketing decisions. Content Preferences & Affinity — genre-preference, content-preference, and single-title affinity modeling (two-tower retrieval with semantic content embeddings) that ranks audiences for upcoming titles and powers cross-channel promotion. What You’ll Bring: Required 5–8 years of industry experience in ML engineering or applied data science (3+ years with a Ph.D.), including a track record of leading projects to production. Deep Python expertise and strong software engineering practices; production experience building and deploying ML at scale (millions+ of users/records). Strong proficiency in Databricks (PySpark, Delta Lake, Workflows/DLT, MLflow, Unity Catalog) and solid SQL/Snowflake experience for feature sourcing and model-output delivery. Experience with AWS ML services (SageMaker, S3, Lambda). Strong understanding of ML model evaluation, A/B testing, and statistical/causal inference; depth in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, forecasting, or optimization. Demonstrated technical leadership: driving architectural decisions, setting patterns/standards, and mentoring other engineers — including leading by influence across teams and time zones. Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent experience). Excellent written and verbal communication, with the ability to advocate technical solutions to engineers, scientists, and product stakeholders. Preferred: Recommendation systems, personalization, identity resolution, or audience modeling in a media / streaming / ad-tech context. Experience with two-tower / retrieval architectures, probabilistic identity resolution (graph-based matching, entity resolution, confidence calibration), and Data Clean Room ML (Snowflake DCR, AWS Clean Rooms). Experience architecting or standardizing components of an ML platform used by multiple engineers or teams. Hands-on experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, MCP), Databricks Genie Space configuration, and Snowflake Cortex. Experience with feature stores (Databricks Feature Store, Tecton, Feast) and contributions to open source or ML publications. Experience partnering with or mentoring globally distributed teams. Our Technology Stack Primary platform: Databricks (Lakehouse, PySpark, Delta, Workflows/DLT, MLflow, Feature Store, Unity Catalog, Asset Bundles, Genie). Cloud: AWS (SageMaker, S3, Lambda). Warehouse: Snowflake (incl. DCR, Snowpark, Cortex). Activation: Mosaic, FreeWheel, Google Ad Manager. Agentic AI: Cursor, GitHub Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, MCP. Languages: Python (primary), SQL, Scala (as needed). Warner Bros. Discovery is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $159,180.00 - $295,620.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. If you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Senior Data Scientist (Data Platform Team), Hyderabad About Warner Bros. Discovery Warner Bros. Discovery is a premier global media and entertainment company, offering audiences the world's most differentiated and complete portfolio of content, brands, and franchises across television, film, streaming, and gaming. The new company combines Warner Media's premium entertainment, sports, and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com. Meet our Team The Data Platform team at Warner Bros. Discovery powers data-driven experiences across global products like Max, Discovery+, Sports, Studios, and News. The team builds and operates a scalable, multi-tenant data ecosystem that enables analytics, real-time insights, and machine learning use cases across the organization. Positioned at the core of the data journey, the team is responsible for ingesting, processing, and transforming large volumes of client and server-side data into reliable and high-quality datasets. Operating at the intersection of data and platform engineering, the team focuses on building robust pipelines, ensuring data quality and governance, and driving innovation in real-time processing, observability, and modern data infrastructure. The team collaborates closely with product, analytics, and engineering stakeholders to enable data-driven decision-making at scale. Roles & Responsibilities: - Design, develop, and deploy machine learning models and data science solutions at scale. - Build ML capabilities using recommendation systems, personalization, predictive modeling, NLP, Generative AI, and Large Language Models (LLMs). - Develop end-to-end ML workflows including data preparation, feature engineering, model training, validation, deployment, monitoring, and optimization. - Apply advanced data science techniques including regression, classification, time series forecasting, causal inference, optimization techniques, and deep learning approaches. - Build and improve scalable ML training and inference pipelines. - Work closely with Data Engineers, ML Engineers, Product Managers, and business teams to deliver data-driven solutions. - Perform experimentation, A/B testing, statistical analysis, and model evaluation to measure model effectiveness. - Research and apply modern ML techniques including Transformers, Deep Learning models, NLP techniques, and AI-based solutions. - Follow and promote data science best practices for model development, evaluation, and deployment. - Mentor junior team members and provide technical guidance when required. - Leverage AI-assisted tools to improve productivity and quality. What to Bring: - Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field. - 5+ years of experience in building data science models and machine learning solutions. - Strong understanding of statistics, machine learning algorithms, probability, and data science fundamentals. - Hands-on experience in developing, deploying, and optimizing ML models in production environments. - Strong programming experience with Python, R, Scala, or similar programming languages. - Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, XGBoost, Keras, and Spark ML. - Strong knowledge of machine learning techniques, including Regression & Classification Models, Time Series Forecasting, Recommendation Systems, Personalization, Search & Ranking Models, Deep Learning, NLP, LLMs, Causal Inference, Reinforcement Learning, Multi-Armed Bandits, and Model Optimization. - Experience across the complete ML lifecycle, including feature engineering, training pipelines, model validation, deployment, monitoring, and continuous improvement. - Experience working with large-scale datasets and distributed computing frameworks. - Good understanding of MLOps concepts, scalable ML architectures, and production ML systems. - Strong analytical thinking, problem-solving abilities, communication skills, and cross-functional stakeholder collaboration experience. Preferred Qualifications - Experience working on personalization, customer growth, advertising, content recommendation, or large-scale consumer platforms. - Exposure to cloud-based ML platforms and production ML infrastructure. - Knowledge of modern AI/GenAI tools and frameworks. - Ability to translate research concepts into practical business solutions. What We Offer: - A Great Place to work - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN. To see what it’s like to work at CNN, follow @WBDLife on  Instagram  and  X ! We are CNN. THE WORLD'S MOST ESSENTIAL AND ENGAGING SOURCE OF DIGITAL NEWS. We are in the midst of rapid transformation and need our next generation of innovators, makers, and dreamers who will lead and drive our growth. We aim to make the world a better, more connected place. About CNN Digital CNN Digital is a global leader in news and information, reaching millions of users daily across web, mobile, and connected TV platforms. Our ML/AI team works at the intersection of journalism, technology, and user experience, building systems that help people discover and engage with the news that matters to them. Your New Role… CNN is seeking a Machine Learning Engineer I to build and deploy ML systems that power personalization, search, recommendations, and content understanding for millions of users across CNN's digital platforms. You will work on production ML systems with measurable product impact, collaborating with cross-functional teams of engineers, data scientists, product managers, and editorial staff. Your Role Accountabilities… - Build and deploy full-lifecycle machine learning systems in Python for CNN digital products, including personalization, search, recommendations, and content understanding - Develop and maintain production ML pipelines, including feature engineering, model training, evaluation, and serving infrastructure - Implement rigorous experimentation and A/B testing frameworks to validate model performance and product impact - Optimize ML systems for real-time, web-scale performance serving millions of users - Partner with platform and infrastructure teams to ensure ML systems meet reliability, scalability, and performance standards - Contribute to code reviews, documentation, and team knowledge sharing Qualifications & Experience… Required Qualifications: - Graduate degree (MS or PhD) in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field - 1+ years of professional experience building and deploying machine learning systems in production environments - Strong Python programming skills and experience with machine learning frameworks (e.g., scikit-learn or similar) - Experience across the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment - Solid understanding of software engineering best practices, including version control, testing, and CI/CD - Ability to collaborate effectively with cross-functional partners - Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders Preferred Experience: - Experience working on large-scale consumer internet products (e.g., social, streaming, e-commerce, media) - Hands-on experience with recommendation systems, search, NLP, or information retrieval - Familiarity with data pipelines, feature stores, or embedding infrastructure - Experience with experimentation platforms, A/B testing, and experimentation analysis - Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes) - Interest in generative AI applications and/or the media and news industry Technical Skills: - Languages: Python (required), SQL - ML Frameworks: scikit-learn or similar - Tools: Git, MLflow or similar MLOps tools - Data: Experience working with large datasets, distributed processing, and feature engineering - Deployment: REST APIs, model serving, monitoring, and observability How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $99,400.00 - $184,600.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. At HBO Max, storytelling takes center stage. We’re one of the world’s most iconic entertainment brands — home to bold originals and unforgettable characters. While audiences binge award-winning content, breaking news, and sports around the clock, our teams stay busy at work creating what’s next in streaming. From Succession, Euphoria, and The Sopranos to global franchises like Game of Thrones and Harry Potter, our content sparks conversation and shapes culture. HBO Max delivers boundary-pushing stories across genres and platforms, connecting millions of viewers across 90 countries globally— and we’re just getting started. We're home to the most talked about shows and movies, granting audiences access to the worlds of HBO, Harry Potter, DC, Warner Bros., ID, Adult Swim, A24, and more. Turn your streaming obsession into a career— we’re hiring! About the Role We're seeking a Senior Machine Learning Engineer to develop and deploy machine learning solutions for consumer growth, including fraud detection, pricing optimization, and user behavior modeling. You'll combine strong technical skills with a passion for learning to build scalable ML systems that drive business impact. This role requires a blend of strong research skills, mathematical rigor, and production-grade engineering practices . You will also act as a mentor to junior scientists, collaborate cross-functionally with product, engineering, and business stakeholders, and advance the company’s research agenda through thought leadership and, when possible, publications in top-tier venues. Key Responsibilities - End-to-End Delivery : Build complete ML pipelines from data processing to model deployment and monitoring in production environments - ML Development : Design and implement machine learning models for growth applications, from classical algorithms to deep learning approaches - Cross-Functional Collaboration : Work closely with product, engineering, and senior researchers to translate requirements into effective ML solutions - Mentorship : Guide junior data scientists and contribute to team knowledge sharing - Research & Innovation : Stay current with ML research and explore new methodologies relevant to consumer growth challenges Required Qualifications - Education : PhD/MS in Machine Learning, Data Science, or closely related field - Experience : 3+ years (PhD) or 5+ years (MS) of hands-on machine learning experience - Technical Skills : - Proficient in Python and ML frameworks ( PyTorch , TensorFlow, Scikit-learn,   XGBoost ) - Experience with SQL and large-scale data processing - Proven   track record   deploying ML models to production - Mindset :   Strong desire   to learn new techniques and adapt to evolving business needs - Communication : Ability to clearly articulate ML concepts to diverse stakeholders Preferred Qualifications - Experience in consumer-facing applications (growth, fraud, personalization) - Familiarity with distributed computing systems (Spark, Ray) - Publications in ML conferences or contributions to open-source projects How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $159,180.00 - $295,620.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Manager, Machine Learning Engineering & Data Science   , Hyderabad About Warner Bros. Discovery: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film,   streaming   and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit   www.wbd.com . Meet Our Team: When we say, “the stuff dreams are made of,”   we’re   not just referring to the world of wizards, dragons. and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating   what’s   next… From brilliant creatives to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Roles and Responsibilities: The Manager – Machine Learning Engineering & Data Science will lead a team of Machine Learning Engineers and Data Scientists responsible for building, deploying, and operating   large ‑ scale   ML systems that power critical business capabilities across consumer platforms. This role brings together Data Science, ML engineering, platform reliability, and people leadership, with the opportunity to shape production ML systems in areas such as   user   behavioral modeling, fraud and abuse detection, transaction intelligence, and lifecycle engagement. This role will also lead the development of ML platform capabilities across the full lifecycle, including pipeline orchestration, experimentation frameworks, model promotion, deployment, and observability, enabling scalable and reliable production ML systems. The role requires strong   hands ‑ on   technical depth, experience in designing data science experiments, architecting scalable ML solutions, and building production-grade systems, along with the ability to scale teams, processes, and platforms. Key Responsibilities - Own end-to-end delivery:   Accountable for delivering ML/DS initiatives from problem definition through production, ensuring timelines, quality, and business impact are consistently met. - Own ML platform and lifecycle capabilities:   Build and evolve core systems for ML pipelines, experimentation, model versioning/promotion, deployment, and observability, ensuring reproducibility, governance, and production reliability. - Be a hands-on technical leader:   Stay close to the work—review designs, guide modeling approaches,   participate   in key technical decisions, and help unblock complex ML and data challenges. - Partner deeply with product and stakeholders:   Work closely with Product, Engineering, and business teams to shape problem statements, prioritize work, and ensure ML solutions align to clear outcomes and KPIs. - Drive execution with operational excellence:   Establish   strong planning, tracking, and risk management practices; ensure ML systems are production-ready with robust pipelines, automated deployment workflows, and end-to-end monitoring/observability. - Set and enforce quality standards:   Own the bar for model performance, data quality, experimentation rigor, and system reliability in production. - Lead and develop the team:   Hire, mentor, and manage a team of MLEs and Data Scientists; provide clear goals, regular feedback, and career development to build a high-performing organization. - Foster collaboration and shared ownership:   Create strong working relationships across teams, improve how ML integrates into broader systems, and drive alignment across cross-functional partners What to Bring: - 12–15 years of total experience with 3+ years of leading and managing ML, Data Science   teams . - Proven experience designing and delivering machine learning-driven, large-scale distributed systems in production . - Experience building or   operating   end-to-end ML platforms, including pipeline orchestration, experimentation systems, model registry/promotion workflows, and production observability. - Experience translating business problems into scalable ML/AI solutions with measurable impact . - Hands-on experience with cloud platforms (AWS, GCP, or Azure) and modern ML/data ecosystems . - Strong understanding of ML platforms, data pipelines, distributed systems, and production architecture patterns . - Ability to collaborate effectively across Product, Engineering, Data, and Business teams . - Excellent written and verbal communication skills with   ability   to contribute to technical design discussions and documentation . Preferred: - Experience working with global, cross-functional teams. - Exposure to   MLOps   /   LLMOps   frameworks, including experiment tracking, model governance, promotion strategies, deployment pipelines, and observability tooling. - Familiarity with modern AI patterns (e.g., GenAI, LLM-based applications, RAG, or applied AI systems) . - Experience   establishing   reusable technical patterns, standards, and scalable frameworks across teams . What We Offer: - A Great place to work. - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role : As the Staff, Solutions Architect (AI/ML) , you will play a pivotal role in driving the adoption of AI and Machine Learning solutions within one of the world’s largest Media & Entertainment companies. Based in India, you will lead the design and implementation of innovative AI/ML architectures that transform how we create, distribute, and monetize content across global markets. Your expertise will help bridge the gap between complex business challenges and advanced technical solutions, ensuring AI initiatives deliver real business value. This is a unique opportunity to work at the intersection of creativity and technology, where you’ll lead the development of intelligent solutions for personalized viewer experiences, optimized content workflows, and data-driven decision-making. If you’re passionate about leveraging AI/ML to revolutionize the Media & Entertainment industry and thrive in a dynamic, collaborative environment, this role is for you. 1. AI/ML Solution Design and Development - Design and develop scalable AI/ML solutions tailored to address business challenges such as audience analytics, content personalization, and ad optimization. - Lead the end-to-end architecture of AI/ML platforms, ensuring seamless integration with existing systems and data pipelines. - Collaborate with data scientists, engineers, and business stakeholders to convert models into production-ready solutions. - Evaluate and select appropriate AI/ML frameworks, technologies, and tools to meet project requirements. - Ensure AI solutions are optimized for performance, scalability, and reliability across diverse use cases. 2. Technical Leadership and Innovation - Provide technical leadership for AI/ML projects, guiding teams through solution architecture, development, and deployment. - Stay abreast of emerging AI/ML trends and technologies to introduce innovative solutions and best practices. - Lead proof-of-concept (POC) initiatives to validate new AI capabilities and demonstrate their potential impact. - Promote a culture of innovation within the team, encouraging experimentation with cutting-edge AI/ML techniques. - Mentor junior architects and engineers to build a strong pipeline of AI/ML talent. 3. Collaboration and Stakeholder Engagement - Act as a key interface between business units, technical teams, and senior leadership to align AI/ML solutions with organizational goals. - Translate business requirements into technical specifications, ensuring clarity and feasibility. - Collaborate with cross-functional teams to prioritize and execute AI/ML projects that deliver the highest business impact. - Communicate the value and progress of AI/ML initiatives to non-technical stakeholders through clear, compelling narratives. - Foster strong relationships with external partners, including technology vendors and academic institutions, to drive innovation. 4. AI Governance and Risk Management - Implement best practices for AI/ML governance, including model explainability, accountability, and ethical use. - Ensure AI solutions comply with data privacy regulations and internal security protocols. - Proactively identify and mitigate risks associated with AI/ML implementations, such as bias, overfitting, or data quality issues. - Develop monitoring frameworks to track model performance and retrain models as necessary to maintain effectiveness. - Establish guidelines and documentation for AI/ML processes, ensuring consistency and transparency. 5. Scalability and Continuous Improvement - Architect solutions that are modular and scalable, capable of supporting future business growth and technological evolution. - Regularly review and optimize existing AI/ML systems for improved performance and cost-efficiency. - Establish feedback loops to capture learnings from deployed solutions and inform future enhancements. - Identify opportunities for automation and operational efficiency using AI/ML. - Lead initiatives to streamline workflows and reduce time-to-market for AI/ML projects. Qualifications & Experiences: Academic Qualifications: - Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical discipline. - Specialized certifications in AI/ML (e.g., Google Cloud AI Engineer, AWS Machine Learning Specialty) are a plus. Professional Experience: - 8+ years  of experience in AI/ML solution architecture, with at least  3+ years  in a leadership role. - Proven track record of designing and deploying AI/ML solutions in enterprise-scale environments, preferably within Media & Entertainment or a similar industry. - Hands-on experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and cloud platforms (AWS, Azure, GCP). - Strong expertise in building and optimizing data pipelines, model deployment workflows, and MLOps practices. - Experience in implementing AI use cases like recommendation systems, natural language processing (NLP), and computer vision. Technical Skills: - Proficiency in programming languages like Python, Java, or R. - Expertise in big data technologies (e.g., Spark, Hadoop) and database systems (SQL, NoSQL). - Solid understanding of microservices architecture and APIs for AI model integration. - Advanced knowledge of AI model lifecycle management, from training to deployment and monitoring. - Familiarity with visualization tools (e.g., Tableau, Power BI) to present AI-driven insights. Soft Skills: - Exceptional problem-solving and critical-thinking abilities. - Strong communication skills with the ability to articulate technical concepts to non-technical audiences. - Collaborative mindset with the ability to work effectively in cross-functional teams. - Leadership qualities, including mentoring and team development. - High adaptability to a fast-paced and dynamic work environment. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Staff Software Engineer – Video AI Team, Bangalore About Warner Bros. Discovery: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet Our Team: When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons, and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands are the storytellers bringing our characters to life, the creators bringing them to your living rooms, and the dreamers creating what’s next… From brilliant creatives to technology trailblazers, across the globe, WBD offers career-defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Roles & Responsibilities: We’re looking for a Staff Software Engineer for our Video AI Team in Bangalore to join the AI/ML organization, focusing on applications of AI to video. The team supports capabilities such as scene segmentation, video annotation, clip generation, metadata enrichment, video understanding, closed captions, translations, subtitles and content classification to help make WBD content truly global. In this role, you will help build a robust, scalable platform that enables the training, deployment, and observability of machine learning models. You will drive platform architecture, lead critical components, and work across teams to establish engineering excellence in the ML infrastructure layer. - Design and lead the development of core components of the machine learning platform with a focus on scalability, reliability, and cloud-agnostic principles. - Build APIs and microservices that power end-to-end machine learning workflows, including model deployment, orchestration, model registry integration, and observability. - Architect and deploy AI/ML pipelines for video ingestion, preprocessing, annotation, training, evaluation, serving, monitoring, and continuous improvement. - Develop cloud-native AI systems on Google Cloud Platform using Vertex AI, Vertex AI Pipelines, Vertex AI Endpoints, GKE, Cloud Run, BigQuery, Cloud Storage, Pub/Sub, and related services. - Own cloud infrastructure and CI/CD automation using Infrastructure-as-Code principles, with hands-on implementation using Terraform, Kubernetes, Docker, and deployment automation tools. - Evaluate, fine-tune, train, optimize, and deploy open-source Computer Vision and Multimodal AI models and Vision Transformers for production use cases. - Design and operationalize Deep Learning, Computer Vision, Generative AI, LLM, VLM, and RAG-based capabilities for video understanding and content intelligence workflows. - Collaborate with content protection and security teams to ensure robust access controls, secure model/data access patterns, and compliance-aligned platform practices. - Champion engineering excellence through well-tested code, clear documentation, design reviews, code reviews, and continuous improvement of development and deployment practices. - Establish and enforce best practices in testing, code quality, monitoring, observability, incident readiness, and reliability for ML pipeline components. - Work closely with AI engineers, data scientists, product managers, and platform teams to support evolving use cases such as scene segmentation, video annotation, clip generation, metadata enrichment, recommendations, and media workflows. - Mentor engineers, influence architecture across teams, and help set long-term technical direction for Video AI platform capabilities. What to Bring - 9–12+ years of software engineering experience building scalable backend systems, distributed services, and cloud-native platforms. - Deep hands-on experience with cloud platforms such as GCP, with the ability to design cloud-agnostic deployment patterns. - Strong hands-on experience with GCP and Vertex AI platforms, including Vertex AI Pipelines, Model Registry, Endpoints, GKE, Cloud Run, BigQuery, Cloud Storage, Pub/Sub, Cloud Monitoring, and Cloud Logging. - Experience working with production deployment of machine learning systems, including model training, evaluation, serving, monitoring, rollback, and lifecycle management. - Strong knowledge of Deep Learning, Computer Vision, and Generative AI models, including practical experience with modern ML frameworks such as PyTorch, TensorFlow, and Hugging Face ecosystem. - Hands-on experience evaluating, fine-tuning, training, and deploying open-source Computer Vision and Multimodal AI models for production use cases, including model optimization, transfer learning, distributed training, and performance benchmarking. - Excellent proficiency in Python with strong software design, API design, and architecture skills. - Strong experience with Terraform, Kubernetes, Docker, containerized deployments, CI/CD workflows, and Infrastructure-as-Code practices. - Experience building APIs, microservices, event-driven systems, and asynchronous processing patterns for large-scale ML workflows. - Experience in building and maintaining observability stacks such as Prometheus, Grafana, distributed tracing, and cloud-native monitoring tools. - Familiarity with model serving technologies such as Triton, TorchServe, vLLM or similar platforms is preferred. - Experience with RAG architectures, LLM/VLM deployment, vector databases, prompt engineering, and GPU-based inference systems is preferred. - Familiarity with Agile development practices, strong operational ownership, and a mindset for reliability, scalability, maintainability, and cost optimization. - Experience collaborating in cross-functional teams and setting engineering standards at scale through technical leadership, mentorship, and documentation. - Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Engineering, or a related field; equivalent practical experience will also be considered. What We Offer: - A Great Place to work. - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. At HBO Max, storytelling takes center stage. We’re one of the world’s most iconic entertainment brands — home to bold originals and unforgettable characters. While audiences binge award-winning content, breaking news, and sports around the clock, our teams stay busy at work creating what’s next in streaming. From Succession, Euphoria, and The Sopranos to global franchises like Game of Thrones and Harry Potter, our content sparks conversation and shapes culture. HBO Max delivers boundary-pushing stories across genres and platforms, connecting millions of viewers across 90 countries globally— and we’re just getting started. We're home to the most talked about shows and movies, granting audiences access to the worlds of HBO, Harry Potter, DC, Warner Bros., ID, Adult Swim, A24, and more. Turn your streaming obsession into a career— we’re hiring! Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) — ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention. At WBD, Machine Learning Engineering does rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks, with strong working knowledge of Snowflake and AWS, and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role: This is a senior, high-ownership US-based role that sits between our Senior MLE and Staff MLE levels. You will own the design and delivery of production ML systems end to end and take on cross-cutting technical leadership: setting patterns, driving key architectural decisions on flagship workstreams, and raising the bar for the broader ML organization — including close partnership with our Hyderabad ML team. As a US-based senior engineer, you will also serve as a technical anchor and time-zone bridge across the global team: framing ambiguous problems, unblocking others, and translating business priorities from US-based Product, Marketing, and Ad Sales stakeholders into an executable ML roadmap. This role is ideal for engineers with roughly 5–8 years of experience (3+ with a PhD) who operate with strong autonomy, lead by influence, and can move fluidly from hands-on modeling and pipeline engineering to architecture and mentorship. You will do meaningful individual technical work while beginning to exercise Staff-level scope across initiatives. What You’ll Do: ML System Design & Technical Leadership Lead end-to-end development of production ML systems: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring. Own one or more flagship ML products — e.g., probabilistic identity resolution (matching unauthenticated device IDs and 1P cookies to households/persons with calibrated confidence), single-title affinity (two- tower retrieval), lookalike modeling, or forecasting — and drive their technical direction. Make and document key architectural decisions across a workstream (feature-store design, training/serving patterns, evaluation frameworks); provide deep trade-off analysis on scalability, latency, reliability, and cost. Design scalable feature and inference pipelines on Databricks (PySpark, Delta, Workflows/DLT, Unity Catalog) integrated with Snowflake and activation systems (Mosaic, FreeWheel, GAM), with documented feature contracts, backfill paths, and freshness SLAs. Establish and evangelize patterns that other engineers adopt; anticipate risks and failure modes before they surface. Modeling & Experimentation Develop and optimize models across the ML spectrum: gradient boosting (XGBoost/LightGBM), embedding/two-tower retrieval, neural ranking, probability calibration (e.g., isotonic regression), and probabilistic/graph- based matching. Design rigorous offline and online experiments; define evaluation frameworks (precision/recall, AUC-ROC, NDCG, decile lift, calibration curves) appropriate to each use case. Apply causal-inference techniques (propensity scoring, uplift/incrementality modeling) to measure true lift of audience targeting on engagement and retention KPIs. Contribute to lookalike modeling (LAL 2.0+) using 1,000+ first- and third- party features, including privacy-safe builds inside Data Clean Rooms (Snowflake DCR). MLOps & Infrastructure Champion MLOps best practices: model versioning, champion/challenger promotion, automated retraining triggers, drift detection, and production monitoring with MLflow on Databricks. Build and maintain robust, reproducible, auditable ML pipelines on Databricks (and AWS SageMaker where appropriate, e.g., the identity- resolution track); enforce leakage prevention and training/serving consistency. Shape the team’s feature-store strategy — feature contracts, backfills, and freshness SLAs — and implement data-quality checks, model-health dashboards, and alerting thresholds. Embed FinOps cost discipline (compute caps, auto-termination, job tagging) into pipeline design. Agentic AI & Modern Development Actively use and advocate for AI-assisted development: Cursor, GitHub Copilot, and Amazon Q for code generation, review, and documentation. Leverage Databricks Genie as a governed natural-language analytics layer — configuring Genie Spaces over ML feature tables and audience datasets to enable self-service exploration for cross-functional stakeholders. Use Snowflake Cortex (Copilot, Cortex Analyst, Cortex Search) to accelerate SQL authoring, data discovery, and RAG-based internal tooling over Snowflake-resident identity and audience data. Design and prototype agentic ML workflows (MCP-compatible tooling, LangChain/LangGraph) to automate repetitive tasks such as data validation, feature selection, and hyperparameter search; evaluate LLM- based approaches for metadata enrichment and content understanding. Mentorship & Cross-functional Collaboration Mentor Senior and MLE 2 engineers — including members of the Hyderabad team — through code reviews, design discussions, and pairing; contribute to and help set team technical standards. Serve as a US-based point of contact and time-zone bridge for the global ML team; help align priorities and unblock the India team across time zones. Partner with US-based Product, Marketing, and Ad Sales stakeholders to translate business requirements into ML problem formulations, and with Data Engineering on data contracts and pipeline SLAs. Communicate model performance, trade-offs, and business impact clearly to technical and non-technical stakeholders. Flagship Projects You’ll Work On Identity Intelligence — foundational, privacy-safe identity across all WBD brands: probabilistic ID resolution that resolves unauthenticated signals to households/persons with calibrated confidence (entity resolution with gradient boosting and embeddings, representation learning, isotonic calibration, candidate blocking, champion/challenger pipelines), expanding addressable audiences beyond deterministic matching. Audience Intelligence — advertising and marketing use cases: lookalike and predictive audiences (LAL across 1,000+ features), ML-driven smart audiences, layered retrieval + propensity, and incrementality/closed-loop optimization, with privacy-safe activation including data clean rooms. ML-based Forecasting — audience growth, demand, and advertising yield/pricing forecasting that powers ad sales and marketing decisions. Content Preferences & Affinity — genre-preference, content-preference, and single-title affinity modeling (two-tower retrieval with semantic content embeddings) that ranks audiences for upcoming titles and powers cross-channel promotion. What You’ll Bring: Required 5–8 years of industry experience in ML engineering or applied data science (3+ years with a Ph.D.), including a track record of leading projects to production. Deep Python expertise and strong software engineering practices; production experience building and deploying ML at scale (millions+ of users/records). Strong proficiency in Databricks (PySpark, Delta Lake, Workflows/DLT, MLflow, Unity Catalog) and solid SQL/Snowflake experience for feature sourcing and model-output delivery. Experience with AWS ML services (SageMaker, S3, Lambda). Strong understanding of ML model evaluation, A/B testing, and statistical/causal inference; depth in one or more of recommendations & ranking, identity resolution, embeddings/retrieval, forecasting, or optimization. Demonstrated technical leadership: driving architectural decisions, setting patterns/standards, and mentoring other engineers — including leading by influence across teams and time zones. Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent experience). Excellent written and verbal communication, with the ability to advocate technical solutions to engineers, scientists, and product stakeholders. Preferred: Recommendation systems, personalization, identity resolution, or audience modeling in a media / streaming / ad-tech context. Experience with two-tower / retrieval architectures, probabilistic identity resolution (graph-based matching, entity resolution, confidence calibration), and Data Clean Room ML (Snowflake DCR, AWS Clean Rooms). Experience architecting or standardizing components of an ML platform used by multiple engineers or teams. Hands-on experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, MCP), Databricks Genie Space configuration, and Snowflake Cortex. Experience with feature stores (Databricks Feature Store, Tecton, Feast) and contributions to open source or ML publications. Experience partnering with or mentoring globally distributed teams. Our Technology Stack Primary platform: Databricks (Lakehouse, PySpark, Delta, Workflows/DLT, MLflow, Feature Store, Unity Catalog, Asset Bundles, Genie). Cloud: AWS (SageMaker, S3, Lambda). Warehouse: Snowflake (incl. DCR, Snowpark, Cortex). Activation: Mosaic, FreeWheel, Google Ad Manager. Agentic AI: Cursor, GitHub Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, MCP. Languages: Python (primary), SQL, Scala (as needed). Warner Bros. Discovery is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request. In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery’s total compensation package for employees. Pay Range: $159,180.00 - $295,620.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation. If you’re a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Your New Role : As Staff, Data Science & Applied AI, you will be a core technical contributor within the Enterprise Data & AI Solutions team supporting Warner Bros. Discovery’s global portfolio — including Studios, Streaming, Linear Networks, Consumer Products, Games, and Direct-to-Consumer platforms. This role is designed for a hands-on expert in applied data science who thrives at the intersection of statistical rigor, machine learning engineering, and business impact. You will translate complex business challenges into scalable analytical solutions, production-grade models, and data products that drive measurable enterprise value. You will operate as a senior individual contributor, partnering closely with Product, Engineering, and Business stakeholders to design, develop, deploy, and scale advanced analytics and AI capabilities across the organization. Key Responsibilities include: Advanced Analytics & Machine Learning - Design, develop, and deploy statistical, predictive, and machine learning models across domains such as customer analytics, forecasting, personalization, optimization, and content performance. - Apply advanced techniques including ensemble methods, gradient boosting, deep learning, NLP, time-series forecasting, and recommendation systems. - Ensure model robustness through rigorous validation, monitoring, and performance tracking. Generative AI & LLM Applications - Design and implement Generative AI solutions leveraging large language models (LLMs) for use cases such as knowledge retrieval, content intelligence, metadata enrichment, summarization, and workflow automation. - Develop and optimize prompt engineering strategies, evaluation frameworks, and guardrails to ensure high-quality, reliable outputs. - Architect Retrieval-Augmented Generation (RAG) pipelines integrating structured and unstructured enterprise data sources. - Fine-tune or adapt foundation models where appropriate using parameter-efficient techniques (e.g., LoRA, adapters) aligned with business needs. - Implement evaluation pipelines to measure hallucination rates, bias, latency, cost efficiency, and model quality in production environments. - Collaborate with Responsible AI and Governance teams to ensure compliance with enterprise AI policies, data privacy standards, and ethical AI practices. Product Ionization & AI Engineering - Collaborate with Data Engineering and DevOps teams to productionize ML and GenAI solutions in scalable cloud environments. - Design CI/CD pipelines for model lifecycle management, including experimentation tracking, versioning, and automated retraining. - Implement monitoring frameworks for model drift, prompt drift, performance degradation, and data integrity. Automation & AI Framework Development - Develop reusable ML and GenAI frameworks, accelerators, and internal utilities that improve productivity across teams. - Advance automation initiatives to reduce manual workflows and enhance analytical velocity. - Stay current with cutting-edge advancements in foundation models, multimodal AI, and agentic architectures to continuously elevate enterprise AI capabilities. Qualifications & Experiences: - Bachelor’s degree, MS, or greater in Computer/Data Science, Engineering, Mathematics, Statistics, or related quantitative discipline. - 8+ years relevant experience in data science, 2+experience in GenAI - Demonstrated track record of delivering production-grade AI/ ML solutions with measurable business impact. Generative AI & Large Language Model (LLM) Expertise - Hands-on experience designing and deploying Generative AI solutions using large language models (e.g., GPT-class models, open-source foundation models, or enterprise LLM platforms). - Strong proficiency in prompt engineering, structured output design, few-shot learning strategies, and systematic prompt optimization - Experience building Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and enterprise data sources. - Familiarity with embedding models, semantic search, and vector stores (e.g., Pinecone, Weaviate, OpenSearch, FAISS, or equivalent). - Experience fine-tuning or adapting foundation models using parameter-efficient approaches (e.g., LoRA, adapters, instruction tuning). - Understanding of LLM evaluation methodologies, including hallucination detection, bias assessment, response quality scoring, and cost-performance trade-offs. - Exposure to multimodal AI (text, image, audio, video) and agent-based workflows is a plus. - Experience working with enterprise AI platforms (e.g., AWS Bedrock, Azure OpenAI, Databricks Model Serving, Snowflake Cortex, or equivalent). - Understanding of Responsible AI principles, data privacy considerations, and model governance requirements in regulated environments. How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.

Welcome to Warner Bros. Discovery… the stuff dreams are made of. Who We Are… When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Staff Data Scientist: About Warner Bros. Discovery: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. For more information, please visit www.wbd.com . Meet Our Team: When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons. and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next… From brilliant creatives to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive. Roles and responsibilities: The Staff Data Scientist will serve as a individual contributor driving the design, experimentation, and delivery of advanced machine learning solutions for media intelligence and localization use cases. This role defines modeling approaches that advance the state of the art, and turns research into scalable, production-ready ML systems with measurable product and customer impact. The ideal candidate brings deep hands-on expertise in applied machine learning, statistical analysis, and evaluation methodologies and drive innovation through data-informed decision-making. Your Role Accountabilities: - Lead end-to-end design and delivery of production-grade Gen AI based Media processing systems that supports language localization capabilities like Closed Captioning, Language translation, or Dubbing. - Lead data science experimentation by designing experiments, defining success metrics, iterating on model improvements, and transitioning validated approaches into scalable production ML pipelines. - Establish and operate robust production evaluation frameworks, covering model quality, drift detection, inference performance, and system-level metrics with and without ground truth. - Lead, mentor, and grow a team of Applied data scientist, Machine Learning Engineers, setting clear technical direction, delivery standards, and career development paths. - Motivate, inspire and create a culture of experimentation and data-driven innovation while constantly striving to be an advocate for doing what is right for our customers What to Bring - 8+ years total experience of building production grade machine learning solutions - Experience in designing machine learning driven, large-scale distributed systems with large scale customer base - Good practical knowledge in modern machine learning lifecycle. - Ability to technically collaborate with partners - Good understanding of machine learning platform Preferred: - PhD, or Master's degree in CS, CE, ML or related fields. - 3+ hands-on experience in any one of following fields: Computer Vision, ASR, Translation or Text-to-Speech technologies. - Working experience with global teams - Experience in patents or publications at top-tier peer-reviewed conferences or journals What We Offer: - A Great Place to work. - Challenging ML problems in Media Domain. - Equal opportunity employer - Fast track growth opportunities How We Get Things Done… This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview. Championing Inclusion at WBD Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.