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AI Automation Engineer (Talent Pool)
Vira Games — незалежна ігрова компанія, що спеціалізується на розробці та видавництві мобільних ігор. Наша команда — це творчий альянс, що об'єднує досвід, креативність, драйвовість та професіоналізм. Ми завжди раді знайомству з талановитими людьми — навіть коли не маємо відкритої ролі. Саме тому створили Talent Pool: щоб познайомитися зі спеціалістами, які поділяють нашу пристрасть до ігор, і бути на зв'язку, коли з'явиться можливість працювати разом. Якщо ти маєш гарний досвід у AI-автоматизації та хочеш, щоб Vira Games стала частиною твоєї кар'єрної історії, будемо раді знайомству вже сьогодні. Що означає Talent Pool? Подавши заявку, ти потрапиш на розгляд нашої рекрутингової команди. Якщо твій досвід відповідатиме напрямам, які ми розвиваємо, ми додамо твій профіль до Talent Pool — і щойно відкриється релевантна позиція, ти будеш серед перших, з ким ми зв'яжемося. Можливо, наша спільна історія не почнеться сьогодні. Але може початися завтра. Чим ти можеш займатися, коли відкриється відповідна роль: - Декомпозувати процеси, формувати беклог автоматизацій з пріоритизацією за впливом/складністю. - Інтегрувати LLM у процеси компанії; розробляти власні MCP-рішення. - Писати скрипти на JavaScript або Python (у т.ч. за допомогою AI-інструментів, наприклад, Claude Code). - Пояснювати свої інженерні рішення: чому саме так і чим це краще за альтернативи. - Підтримувати й розвивати наявні автоматизації, обробляти помилки. - Писати документацію до рішень. - Слідкувати за AI-трендами й приносити в роботу те, що дає реальну користь. Ми будемо раді познайомитися, якщо ти маєш: - Реально запущені в проді автоматизації/агенти (не лише туторіали) - можеш показати й пояснити. Особливо цінно на n8n. - Розуміння, як працює код: читаєш, пояснюєш, лагодиш і свідомо спрямовуєш його (у т.ч. код від AI). База в Python або JavaScript. - Практичний досвід інтеграцій LLM API: function/tool calling, structured outputs, робота з JSON. - Досвід побудови AI-агентів; розумієш, чим агент відрізняється від одного промпта. - Практичний досвід роботи з REST API: методи, статус-коди, автентифікація, вебхуки. - Досвід забезпечення надійності: логи, метрики, сповіщення; повтори з паузами; безпечні повтори без дублів. - Уміння декомпозувати процеси, визначати межі MVP та чітко описувати вимоги. - Уміння пояснити, ЧОМУ обрано саме таке рішення і чим воно краще за альтернативи. - Досвід документації створених рішень і взаємодії з нетехнічними командами. - Інженерні рішення з огляду на надійність, безпеку та масштабованість. Що буде після відгуку? Ми обов'язково розглянемо твій відгук та уважно ознайомимося з твоїм досвідом. Якщо він відповідатиме напрямам, для яких ми зараз формуємо Talent Pool, ми додамо твій профіль до нашої бази кандидатів і зв'яжемося з тобою, щойно відкриється відповідна позиція. Якщо ж релевантного збігу поки не буде, ми теж повідомимо тебе про результат розгляду. Що ти знайдеш у Vira Games: Бенефіт-кафе — персональний бюджет на страхування, навчання, спортзал чи будь-що для твого балансу. Бонуси за досягнення — ми цінуємо прагнення до досконалості й командну гру, тому відзначаємо помітні результати, ініціативу та реальний вплив. Remote First — працюй з будь-якої точки світу. У Vira Games віддалена робота — це стандарт, а не виняток. Вплив на бізнес — мінімум бюрократії та максимум свободи дій. Можливість впливати на
Deployed Engineer (South EMEA)
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos - Native French Speaker NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM ev
Member of Technical Staff - Software Engineering C...
About Us Preference Model is automating ML engineering and a critical component is models' abilities to develop software. The way we build software is changing fast. Five years ago we wrote every line of code by hand. Today, we don't.
Member of Technical Staff - Machine Learning Infra...
About Us Preference Model is building automated ML research engineering. Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions.
Member of Technical Staff - Low Level & Kernels Ca...
About Us Preference Model is building automated ML research engineering. Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions.
Member of Technical Staff - Research & Post-traini...
About Us Preference Model is building automated ML research engineering. Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions.
Member of Technical Staff - Machine Learning Capab...
About Us Preference Model is building automated ML research engineering. Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions.
Research Engineer
Salary range - $250k - $350k | Equity - up to 0.5% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7.
Research Engineer – AI
About Primary Far too few of the world's best journalists get the recognition, audience, or rewards their work deserves. Primary is building the infrastructure to change that. Primary Index is the first AI-native ranking system for journalism — the credibility standard for news in the AI economy. We evaluate individual journalists on the accuracy, depth, and craft of their published work through a purpose-built AI operating against a transparent, published methodology.
Research Engineer
Console is building the AI agents that power autonomous enterprises. We use AI to autonomously resolve IT, HR, Legal, Finance, Security, and Ops tasks the moment they come in from Slack or Teams. We're building toward a future where enterprise operations are fully autonomous; with no tickets, approvals, or manual processes slowing companies down. Our platform enables companies like Databricks, Figma, and Cursor to delegate entire categories of work to AI agents that understands their org, takes action across systems, and gets smarter over time.
Internal Communications Manager
Perplexity is seeking an Internal Communications Manager to build that function from the ground up. You will own how information moves through Perplexity. You will be responsible for what Perplexity employees think, feel, know, and do. This is a 0→1 role with executive exposure from day one. If you believe internal comms is a strategic function and want to shape how an n(1) company talks to itself, this role is for you. Responsibilities - Listen and learn across the company. Understand what’s happening, how, and why in order to make sound recommendations on what should be amplified or addressed. - Run all-hands and executive content. Planning, execution, measurement, and evolution. - Internal storytelling. Turn strategy, launches, and hard decisions into messages that bring clarity to every team. - Be the signal in noise. Cut through Slack sprawl. Establish the channels, cadences, and norms that keep a fast company informed without drowning it. - Own change management. Deliver hard and easy news with equal clarity and candor. Earn trust for the message and the messenger.. - Protect the culture. Words set the tone. Make sure ours sound like us as we grow. - Measure what matters. Perplexity is a high-velocity high-humility organization. - Partner across the company. Work with every team, brief executives directly, and earn standing as a truth-teller. Qualifications - 6+ years in internal, executive, or corporate communications, ideally inside a high-growth technology company. - A builder, not a maintainer. You've stood a function up, not just kept one running. - World-class writing and editing. You can ghostwrite for an executive, draft an all-hands, or defuse a sensitive announcement in any voice or format. - Proven change-management instincts. You've delivered complex news to a whole company and kept trust intact. - Sharp judgment under pressure. You decide fast, say the hard thing kindly, and hold the line on quality on launch day. - Comfort with executives who hold a strong vision. You can advise, challenge, and make recommendations to senior leaders without flinching. - Deep familiarity with the rules of corporate comms, and a clear point of view on which ones to break and when. - Comfort using AI tools in your workflow, and the ability to say exactly where and how you use them. - A passion for the truth well-told
Research Engineer, Production Model Post-Training
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: - Implement and optimize post-training techniques at scale on frontier models - Conduct research to develop and optimize post-training recipes that directly improve production model quality - Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation - Develop tools to measure and improve model performance across various dimensions - Collaborate with research teams to translate emerging techniques into production-ready implementations - Debug complex issues in training pipelines and model behavior - Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: - Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities - Adapt quickly to changing priorities - Maintain clarity when debugging complex, time-sensitive issues - Have strong software engineering skills with experience building complex ML systems - Are comfortable working with large-scale distributed systems and high-performance computing - Have experience with training, fine-tuning, or evaluating large language models - Can balance research exploration with engineering rigor and operational reliability - Are adept at analyzing and debugging model training processes - Enjoy collaborating across research and engineering disciplines - Can navigate ambiguity and make progress in fast-moving research environments Strong candidates may also: - Have experience with LLMs - Have a keen interest in AI safety and responsible deployment We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role. The annual com
Enterprise Customer Support Specialist
Perplexity is an AI-powered answer engine used to solve billions of queries every month. We build accurate, trustworthy AI that powers decision-making for curious people and organizations worldwide. We are looking for an experienced Enterprise Customer Support Specialist who can marry deep product expertise with a passion for scaling world-class support through automation. You will be the primary advocate for our Enterprise Pro customers, helping them maximize value, troubleshooting complex issues, and feeding their insights straight into future product development. RESPONSIBILITIES - Work directly with enterprise customers—via tickets, Slack, and sometimes calls—to diagnose and resolve their most complex technical and product questions, acting as the “last line of defense” before Product and Engineering step in. - Leverage Perplexity’s own AI tooling and workflow automations to democratize world-class support at scale, continuously identifying opportunities to replace repetitive tasks with agentic, self-service solutions that feel personalized. - Build durable relationships with Enterprise users, advising on best practices, capturing structured feedback, and championing customer needs in roadmap discussions. - Own end-to-end troubleshooting: reproduce issues, isolate root causes, collaborate with engineers, and communicate clear, low-jargon explanations. - Design and maintain detailed use-case flows, playbooks, and internal runbooks that empower teammates and customers to solve recurring challenges faster. - Create and update external documentation (FAQs, help center, guides, tutorials) and internal knowledge bases to ensure information is discoverable and up-to-date. - Track and report support KPIs (response time, CSAT, resolution rates) and propose data-driven process improvements. - Participate in an on-call rotation—including some holidays or weekends—to guarantee timely global coverage. REQUIREMENTS - Minimum 3+ years in B2B enterprise customer support with exposure to U.S. and E.U. markets, or similar fast-paced tech environments. - Hands-on experience prompting large-language models, plus a solid grasp of AI fundamentals (tokens, context windows, embeddings, latency vs. cost trade-offs, etc.). - Ability to translate complex technical concepts—APIs, SSO/SAML, cloud integrations—into clear, actionable guidance for non-technical stakeholders. - Demonstrated strength in critical thinking, rapid context-switching, and ruthless prioritization when juggling multiple escalations1 https://openai.com/careers/ai-technical-support-specialist/. - Proficiency with modern support platforms (Intercom, Zendesk, Jira) and basic data-analysis tools (e.g., SQL, Looker, Snowflake). - Exceptional written and spoken English; business-level fluency in at least one additional language such as Spanish, French, or German is strongly preferred. - Passion for continuous learning, high ownership, and a “do-what-it-takes” mindset in ambiguous situations. BONUS POINTS - Prior experience supporting AI, search, or knowledge-management products. - Familiarity with payment platforms (Stripe), enterprise identity (SSO/OAuth), and API integrations. - Knowledge of enterprise cloud-storage ecosystems (Google Drive, SharePoint, Dropbox) and data-governance best practices. WHY PERPLEXITY? - Impact at Scale – Your work directly influences hundreds of enterprise clients and millions of end-users at an unprecedented scale to encourage personalized support - Velocity & Ownership – Ship improvements quickly in a culture that values curiosity, speed, and quality - Cutting-Edge Tech – Operate at the forefront of applied LLMs and help invent how AI can redefine customer support itself.
Commercial Account Executive
Perplexity is seeking a highly motivated and skilled Commercial Account Executive to join our small but mighty Enterprise team. In this role, you will be responsible for driving new business growth across small and mid-sized organizations, converting product-led demand into committed Enterprise relationships, and building Perplexity's footprint across thousands of high-potential accounts. This role is ideal for proactive sales professionals who thrive at the intersection of technology and business, and who want to help shape Perplexity's commercial motion from the ground up. RESPONSIBILITIES - Drive new business by prospecting, pitching, and closing Perplexity Enterprise solutions with small and mid-sized organizations - Convert existing self-serve customers into Enterprise relationships, and land net-new logos through outbound, inbound, and product-led signals - Diligently research prospects, develop account strategies, and execute outreach campaigns tailored to company and industry needs - Conduct high-impact product demonstrations and respond to technical inquiries across Perplexity's full product suite - Lead client engagement through the entire sales cycle, from initial presentation, technical evaluation, negotiation, to closing and onboarding - Quickly diagnose account potential, qualify in and out with discipline, and partner with Enterprise AEs when an account warrants a larger motion - Collaborate closely with Product, Marketing, and Customer Success to ensure customer satisfaction and solution fit - Maintain up-to-date knowledge of Perplexity's platform, industry trends, and competitor landscape - Meet or exceed individual and team revenue, logo, and activity targets on a monthly and quarterly basis - Maintain accurate records of pipeline and account activity using CRM tools QUALIFICATIONS - Full-cycle SaaS sales experience with a strong track record of closing new business - Proven record of meeting or exceeding revenue targets in a high-growth environment - Skilled at running efficient sales cycles and tailoring messaging to different buyer personas and decision makers - Proven success outbound prospecting into small and mid-sized organizations - Exceptional written and verbal communication; comfortable presenting to executives and technical buyers - Adept at identifying client pain points and mapping solutions that drive business value - Ability to collaborate effectively with both cross-functional teams and technical stakeholders - Experience with CRM systems (e.g. Salesforce) - Bachelor's degree or equivalent experience
AI/ML Engineering Manager
ABOUT THIS ROLE CORSAIR is building a production-grade AI/ML capability spanning intelligent automation, agentic systems, predictive analytics, and data engineering. As AI/ML Engineering Manager, you will lead a team while staying hands-on as a technical contributor. You will architect and build AI/ML systems that directly affect how the business operates, engage stakeholders across functions to surface automation opportunities, and own the full AI/ML lifecycle end-to-end WHAT YOU WILL DO Technical Leadership (40%) - Lead and manage a team of engineers and contractors across multiple AI/ML and automation workstreams; own delivery standards, architecture quality, and team development - Architect agentic AI systems end to end: multi-agent orchestration, tool use, memory management, human-in-the-loop controls, and evaluation frameworks - Own the AI/ML technical roadmap; evaluate build vs. buy tradeoffs and align with VP-level stakeholders - Engage business stakeholders across functions to map workflows, identify automation opportunities, and translate operational requirements into AI-driven solutions Individual Contribution (60%) - Design and ship production-grade agentic AI systems using modern LLM orchestration frameworks; own orchestration logic, state management, and output evaluation - Build durable, fault-tolerant automation pipelines using workflow orchestration tools such as Temporal; design for reliability, retry logic, and long-running distributed tasks - Develop and deploy predictive ML models; own the full lifecycle from feature engineering through production monitoring - Implement RAG systems, vector retrieval pipelines, and prompt engineering strategies at scale; apply LLM fine-tuning when it delivers better ROI than retrieval or prompting - Build and maintain data engineering pipelines (dbt, Dagster, Spark, Microsoft Fabric); diagnose data quality issues that affect AI system reliability - Own MLOps infrastructure: experiment tracking, model versioning, retraining pipelines, and drift detection WHAT YOU BRING Required - 6+ years in AI/ML engineering or applied data science, with at least 1-2 years in a technical lead role - Proven experience designing and deploying agentic AI systems in production: orchestration, tool use, memory, and evaluation - Strong Python and SQL; hands-on with LLM frameworks (LangChain, LangGraph, CrewAI, Strands, or equivalent) and cloud AI platforms (AWS Bedrock, Azure AI Foundry, or Microsoft Fabric) - Experience with durable workflow orchestration tools such as Temporal, Airflow, or Step Functions - Solid ML fundamentals and end-to-end pipeline ownership; experience with data engineering tooling (dbt, Dagster, Spark) - Demonstrated ability to lead engineers technically and communicate tradeoffs to VP-level stakeholders Preferred - Experience in gaming, consumer electronics, or hardware/peripherals - Familiarity with LLM fine-tuning (LoRA, PEFT), vector databases, generative AI for images, or MLOps tooling (MLflow, W&B) - Exposure to Docker, Kubernetes, and CI/CD pipelines for ML workloads - Experience working cross-functionally with Product, Finance, Legal, and Operations stakeholders <span style=
Data Scientist
BETER is an international product group of companies operating in the B2B segment, specializing in fast sports and esports tournaments and technological solutions for their distribution. BETER is the exclusive rights holder of tournament products, broadcasting rights, and official data, and ensures their organization through professional tournament operators, including Setka Cup and ESportsBattle, which conduct official sports and esports events in accordance with established standards and under the auspices of relevant federations and regulatory requirements. We are looking for a Data Scientist who is eager to proactively identify opportunities to improve and automate our business using data science and machine learning. You will work within a small, dedicated team of data scientists collaborating closely with backend engineers, other departments, and end users, while being part of a larger ecosystem of trading and technology experts. In this role, you will design, develop, and optimize predictive models, implement anomaly detection systems, and participate in building production-grade machine learning solutions that directly impact trading and operational processes. You’ll also get hands-on experience with (or apply your existing knowledge of) high-performance architectures, including Kafka, serverless functions, databases, CI/CD pipelines, Kubernetes, and Docker. Responsibilities: - Develop and refine mathematical and statistical models for predicting sports and e-sports outcomes. - Communicate with end users, collect feedback, and build technical solutions based on it. - Apply machine learning to improve trading strategies, automate workflows, and detect anomalies. - Proactively identify opportunities to use data science for business optimization and process automation. - Perform large-scale historical data analysis to generate insights and improve model performance. - Collaborate with backend engineers to build and maintain production machine learning systems . - Research and prototype new methods for expanding into new sports and markets. KPIs for This Role: - Delivery of production-ready machine learning models and pipelines for trading within agreed timelines. - Improvement in model accuracy and reliability, measured against established benchmarks. - Reduction of manual intervention in trading workflows through automation initiatives. Requirements: - 5+ years of experience in data science, analytics, or a related field. - Proficiency in Python (pandas, numpy, scikit-learn, etc.) and working with databases. - Strong knowledge of statistical modeling, probability, and machine learning techniques (Supervised Learning, Unsupervised Learning). - Experience with XGBoost/LightGBM. - Experience with large-scale data analysis and building actionable insights. - Ability to work collaboratively in a cross-functional team and communicate results clearly. - English level - Upper-intermediate and higher. Nice-to-Have: - Experience in the sports or betting industry. - Experience with PyTorch/Tensorflow. - Familiarity with real-time data processing (Kafka, streaming systems). - Exposure to building data pipelines and integrating ML models into production systems. - Knowledge of advanced ML techniques (e.g., ensemble methods, time-series forecasting, anomaly detection). We offer: - Ability to work remotely. - Competitive and timely payment for services. - Flexible work schedule. - Personal mentoring and coaching. - Team building and corporate events. - 100% paid sick leave. - 20 working days of
Lead Machine Learning Engineer
PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION We are seeking a Principal ML Engineer who operates with high autonomy to drive our AI systems for game development. You will operate as an Individual Contributor (IC), owning the lifecycle from experimental PoCs to production-scale deployment. This is an Applied AI role. You won't just be researching; you will integrate state-of-the-art models into tooling for artists and developers, balancing fine-tuning with inference optimization to solve real production bottlenecks. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Responsibilities - Agent Architectures: Design and build complex agent workflows using frameworks like LangGraph/LangChain, leveraging MCP, RAG/GraphRAG, and custom skill integration. - Generative Content Pipelines: Architect Gen2D/Gen3D/video generation workflows (Stable Diffusion, Open Source LLMs) that integrate seamlessly with DCC tools and game engines. - Production Engineering: Move beyond notebooks. Build robust evaluation frameworks and deploy efficient, cost-effective systems using Python, FastAPI, AWS (SageMaker/Bedrock), and MLOps best practices. - Technical Scoping: Navigate ambiguous problems by building PoCs to validate feasibility. Collaborate with product and creative teams to translate technical constraints into realistic roadmaps. Qualifications • Experience: 7+ years building production systems (ML/AI focus), with a proven track record of shipping code — or demonstrably equivalent transferable experience. • Technical Depth: Demonstrable expertise in Agent Architectures or Generative Content workflows (or both). • Comfort with Ambiguity: You don't wait for a spec sheet. You enjoy exploring a blank canvas, building a prototype, and iterating until the path forward is clear. • Pragmatism: Ability to determine when to use off-the-shelf models vs. fine-tuning vs. simple scripts. • Stack Familiarity: Strong proficiency in Python, with experience in AWS, LangChain/LangGraph, ComfyUI, or similar modern AI stacks. About the team • The headquarters of Virtuos: play an active role in the future of the company • Be a part of the R&D center and work with cutting edge technology for gaming • Group outings and activities • Comprehensive medical healthcare provided for all staff • Relocation support • Career and international mobility opportunities with Virtuos Internal Mobility Program • Access to various in-house and external learning opportunities People matter. Diverse opinions and experiences matter. At Virtuos, our talented teams are the cornerstone of our success, and we recognize that fostering and advocating for inclusivity is at the center of what we do best - we make games better, together. Virtuos is proud to be an equal opportunity employer that embraces diversity of thought, expression, culture, and backgrounds. About us Founded in 2004
Machine Learning Engineer with an Agentic Focus
We are looking for a Machine Leaning Engineer (MLE) to design, build, and optimize our machine learning operation. You will play a crucial role in scaling AI models from research to production, ensuring smooth model deployment, monitoring, and lifecycle management across our Google Cloud Platform (GCP) infrastructure. You'll work closely with data scientists, ML Ops, and data engineers to automate workflows, improve model performance, and ensure reliability for our AI that serves millions of players worldwide. What You'll Do - Design, develop, and deploy machine learning models and solutions, leveraging tools such as LangGraph and MLflow for orchestration and lifecycle management. - Collaborate on building and maintaining scalable data and feature pipeline infrastructure for real time and batch processing using tools like BigQuery, BigTable, Dataflow, Composer(Airflow), PubSub, and Cloud Run to support ML model training and inference. - Develop and implement robust strategies for model monitoring and observability to detect model drift, bias, and performance degradation, leveraging tools like Vertex AI Model Monitoring and custom dashboards. - Optimize ML model inference performance to improve latency and cost-efficiency of AI applications. - Ensure the overall reliability, performance, and scalability of the ML models and data infrastructure platform, including proactive identification and resolution of issues related to model performance and data quality. - Troubleshoot and resolve complex issues impacting ML models, data pipelines, and production AI system. - Ensure AI/ML models and workflows meet data governance, security, and compliance requirements, specifically for real-money gaming. What We're Looking For - 1+ years of experience as an ML Engineer, with a focus on developing and deploying machine learning models in production environments. - Strong experience in Google Cloud Platform (GCP), including services relevant to ML and data infrastructure such as BigQuery, Dataflow, Vertex AI, Cloud Run, and Pub/Sub and Composer (Airflow). - Solid grasp of containerization (Docker, Kubernetes) and experience with Kubernetes orchestration platforms like GKE for deploying ML services. - Experience building and deploying scalable data pipelines and machine learning models in production environments. - Understanding of model monitoring, logging, and observability best practices for ML models and applications. - Experience in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Familiarity with AI orchestration concepts using tools like LangGraph or LangChain is a bonus. - Bonus experience includes working in gaming, real-time fraud detection, or AI personalization systems and Agentic workflows.
Real Estate Program Coordinator
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Real Estate Program Coordinator to partner with Anthropic's Global Head of Real Estate & Workplace. This is a high-impact, execution-focused role that keeps Anthropic's rapidly growing global real estate portfolio moving. The Coordinator owns the tactical workstreams behind every new office and every active transaction: initial security deposit and first-month rent wire transfers, monthly rent PO setup with AP, Letters of Credit, and the day-to-day triage of activity coming from our broker team. The ideal candidate is highly organized, detail-obsessed, comfortable juggling many concurrent workstreams across global time zones, and brings a strong service mindset paired with crisp written communication. Reporting directly to the Global Head of Real Estate & Workplace as an individual contributor, you will be the operational engine that ensures our real estate program executes flawlessly as we scale. Key responsibilities New Office Setup & Transaction Execution - Own the work of setting up new offices end-to-end, including initial security deposit and first-month rent wire transfers in partnership with Finance, Accounts Payable, and local brokers. - Manage end-to-end execution of Letters of Credit, including intake forms, supporting documentation, signature collection; review checkpoints with Accounts Payable and the Head of Real Estate before submission. - Track required documentation for international transactions (Articles of Incorporation, Company Tax IDs, Powers of Attorney, passports, banking details) and coordinate with Legal to source missing items. - Maintain real-time status of all open transactions and provide weekly updates to the Head of Real Estate and broker partners. Ongoing Rent & AP Operations - Partner with Accounts Payable to set up purchase orders for monthly rent payments across the portfolio, ensuring accurate amounts, terms, and lease references. - Process and reconcile vendor invoices for rent, TI reimbursements, capital contributions, and broker fees; partner with AP and Corp Accounting on processing and follow-through. - Update and reissue POs as leases are amended, renewed, or escalated. Broker & Portfolio Triage - Serve as the day-to-day operational point of contact for the broker team, triaging incoming activity, requests, and updates across the global portfolio. - Surface decisions needed from the Head of Real Estate, and keep the team focused on what matters most each week. - Track action items, follow-ups, and open questions across every active broker workstream so nothing falls through the cracks. - Build and maintain the Real Estate pipeline tracker in Airtable, including views, automations, versioning, and stakeholder-facing reporting. - Track required documentation across the portfolio (executed leases, amendments, LOIs, NDAs) and ensure executed copies are filed and circulated to relevant partners. Cross-Functional Coordination & Communication</stro
Member of Technical Staff (Model Behavior)
About the Role We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models. The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products.
Staff Applied AI Engineer
About the role Scale's Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. As a Staff Applied AI Engineer, you'll raise the bar for how AI gets built, governed, and evaluated across the team. You'll define standards that other engineers adopt, such as evaluation methodologies for agents and MLOps practices, while acting as the senior technical voice for the most sensitive AI decisions our clients face. What you'll do Define standards for responsible AI, model governance, and production MLOps that get adopted broadly across the Global Public Sector team Build or validate the highest-risk parts of strategic AI systems and use those systems to establish standards other teams can adopt.
Engineering Manager, Infrastructure
At Scale AI, our mission is to accelerate the development of AI applications. For 10 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.
Software Engineer - Evals
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure.
Sr. Security Engineer - GRC Frameworks & AI Govern...
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure.
Member of Technical Staff - Imagine Model
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure.
Member Of Technical Staff - Cloud Infrastructure
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure.
ML Infrastructure Engineer
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure.
AI Product Manager (Coding/Multimodal)
Scale is the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. We are looking for an AI Product Manager to support Multimodal & Coding AI data verticals, including audio, image, video, and world models. This role is designed for someone early in their product career who is excited about AI and wants to develop into a full AI Product Manager over time.
AI Infrastructure Engineer, Serving Platform
As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments. The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.
Manager, Research Scientist
Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications. As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era.
Director of Engineering, Physical AI
Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment.
AI Applications Ops Lead, GPS
Role Overview Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.
Principal AI Ops Architect, GPS
Role Overview Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Principal AI Ops Architect, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.
Senior AI Engineer
PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION We are looking for a Senior AI Engineer to help design and deliver agentic AI systems that power R&D tooling for video game asset pipelines and production workflows. You will help shape the technical direction of our internal agent platform and drive engineering practices around agent loops, memory, evaluation, and safe deployment of LLM-driven applications. This is a senior, hands-on individual contributor role: you will write code, help design the agentic architecture, and partner with stakeholders across studios to turn emerging AI capabilities into production-grade tools. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Responsibilities Agent platform - Design and build key parts of our internal agent libraries - the core abstractions and developer ergonomics that let teams across the company build agents quickly and consistently. - Help shape the architecture of our central agent runtime - the runtime, registry, and observability surface where agents are deployed, monitored, and governed. - Help define and evolve the agent loop / harness: prompt orchestration, tool invocation, sub-agent delegation, and recovery behavior. - Bring in reference patterns from the broader ecosystem (e.g. open-source agent loops and harness projects) and adapt them to our use cases. Agent loop & harness engineering - Drive prompting strategy at scale: system prompt design, guardrails, mitigation of context poisoning and pollution, and management of hyperparameters (context window sizing, lost-in-the-middle effects, temperature, top-k). - Design tool interfaces for agents: MCP servers, structured inputs/outputs for context, and sub-agent composition patterns. - Advocate for best practices for typed-agent frameworks, with first-class observability and telemetry baked into every agent. - Evaluate and integrate local LLM options where latency, cost, or data-residency requirements demand it. Agent memory - Design and build the key parts of the memory layer used across our agents: conversation history management, context chaining, and episodic memory. - Help define the boundary between short-term working context and long-term persistent memory, including decay/retention policies. - Apply RBAC and tenant isolation to memo
Senior Software Engineer, AI Game Creation Platfor...
Introduction At Ironbelly, we are fundamentally changing how video games are made. Our AI team, led by industry luminaries and veterans, is building GameFrame AI —a platform that allows developers to create complex, professional games using natural language. We are the creators of a battle-tested gameplay framework that has been used to build and launch AAA games, and we're leveraging that expertise to architect the future of creative software. This isn't just another AI wrapper. You'll be engineering a production-scale AI orchestration system that coordinates specialized agents to manipulate Unreal Engine in real-time, building technology that has never existed before. A Note on the Role: This is an Applied AI Engineering Position To ensure we're connecting with the right candidates, let's be clear about the focus of this role: - ✅ We ARE looking for: A seasoned backend/platform engineer with production experience building complex systems that use AI models and frameworks (like LangChain, LLM APIs, LLM workflows). - ❌ This is NOT: A Machine Learning research or AI model-building role. We are not developing novel neural network architectures or training models from scratch. What You'll Build 🛠️ As a Senior Software Engineer on our AI Platform, you will architect the intelligent backend that enables conversational game development. - Advanced Multi-Agent Orchestration: Design and build the core of GameFrame AI, implementing sophisticated multi-agent (LangGraph Swarm) and single-agent (ReAct) systems that translate user requests into concrete game development actions. - Gameplay Framework Integration: Engineer the crucial link between our AI systems and Unreal Engine, developing a robust translation layer that allows AI agents to programmatically configure our proprietary, component-based gameplay framework. - Production AI Infrastructure: Architect and scale a distributed, multi-user backend on cloud infrastructure (AWS/GCP, Kubernetes). You'll build everything from multi-provider LLM orchestration and hybrid memory systems to real-time streaming responses over WebSockets. - System Reliability & Observability: Implement enterprise-grade observability, monitoring, and robust failover systems required to support thousands of concurrent users with sub-second response times. Who We're Looking For 💻 We are seeking a strong software engineer who is passionate about building at the intersection of AI and game development. Must-Have Experience: - Expert-Level Backend Engineering: Deep, production-level experience in Python (3.11+), building microservices with frameworks like FastAPI, and designing with async/await patterns. - Production Systems: Proven experience with PostgreSQL, Redis, real-time WebSocket systems, and container orchestration using Docker and Kubernetes in a cloud environment (AWS/GCP). - Applied AI Systems: 1+ years of hands-on experience building applications that leverage AI systems. You have practical, high-level experience with frameworks like LangChain/LangGraph and tooling like Claude Code. - Game Development Context: A strong understanding of Unreal Engine concepts (Actors, Components, Blueprints) and workflows, gained through at least 2 years of professional or significant personal project experience. Nice-to-Have Experience: - Experience building production React applications with TypeScript and Next.js. - Advanced p
Senior Machine Learning Engineer
PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Responsibilities - Agent Architectures & Smart Systems Design and develop intelligent agents using frameworks like LangChain, LangGraph, and similar. Integrate tools via Model-Context-Protocol (MCP)—bonus if you’ve worked with DCC tools such as Blender, Maya, or Unreal. Tackle advanced agent topics: context engineering, memory, planning, and model routing strategy. Collaborate with game and art teams to connect AI agents with production pipelines. - Generative 2D/3D Content Build, customize, and maintain Gen2D/Gen3D/video generation workflows (ComfyUI or similar). Train and deploy generative models (e.g., Stable Diffusion, Qwen). Integrate generative workflows with DCC and creative tools. - Delivering Production-Quality Systems A core part of your role will be taking ideas, prototypes, or research code and turning them into reliable, maintainable, and production-ready systems. Write clean, well-documented code that follows best practices. Work with other engineers and artists to continuously strengthen our deployed ML solutions. Qualifications - Preferred Tech Stack/Tools (Not required, but helpful if you have experience with any of the following) AWS, SQL (especially for retrieval-augmented generation/RAG), FastAPI, ComfyUI, GitLab. Knowledge of game development, art creation, or digital content production pipelines. - What Will Help You Stand Out Experience building agent architectures and/or generative workflows and bringing them to production is strongly preferred. Familiarity with tool integration protocols (like MCP) and DCC environments (Blender, Maya, Unreal, etc.). Interest or experience in gaming, art creation, or creative tech pipelines. Strong problem-solving skills, collaborative approach, and eagerness to learn new technologies About the team • Work alongside industry veterans • A total of 14 different nationalities working together • Live and work in an exciting, cosmopolitan city • Contribute to the world’s biggest AAA games • Customized training programs and regular workshops • Group fitness, wellness activities • Reasonable and flexible working hours • Gaming corners with consoles and canteens on every floor • Comprehensive medical healthcare provided for all staff • Relocation support provided • Career and international mobility opportunities with Virtuos Internal Mobility Program People matter. Diverse opinions and experiences matter. At Virtuos, our talented teams are the cornerstone of our success, and we recognize that fostering and advocating for inclusivity is at the center of what we do best - we
Junior AR Finance Analyst (AI Enablement)
PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION Support day-to-day Accounts Receivable operations while partnering with Finance Ops / Systems to implement AI-enabled automation (e.g., invoice validation, cash application support, collection follow-ups). The role combines AR execution + process improvement. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Responsibilities AR Operations - Issue invoices and supporting documents according to contract terms (milestone / T&M / fixed fee) and internal billing calendar. - Perform cash application : match receipts to invoices, resolve unmatched items, and maintain clean customer ledgers. - Maintain AR aging and follow up with internal stakeholders on billing blockers (PO, acceptance, supporting docs). - Support collections by preparing customer statements, sending reminders, and tracking dispute status. - Assist month-end closing: AR reconciliations, accrual support, and reporting pack inputs. AI / Automation Enablement Ability to translate finance workflows into system logic or automation rules and assist with manager to govern AI agent use cases, such as: - Automated invoice validation (contract vs invoice vs supporting docs). - Invoice bots. - Collection prioritization and reminder workflows. - Exception handling (short-pay, deductions, invalid tax invoice, missing acceptance). - AR anomaly detection (aging spikes, payment pattern deviations). - Translate AR policies into decision trees / rules and ensure appropriate approvals and audit trails. - Partner with Finance system/IT to define requirements (data fields, triggers, exception routing, reporting). - Establish controls: QA checks, sampling reviews, “human-in-the-loop” approvals for sensitive actions. - Maintain SOPs, training materials, and adoption metrics for automation. Qualifications Qualifications - Bachelor’s degree in Accounting, Finance, Business, or related field. - 1–3 years experience in AR / Billing / Cash Application (internship acceptable with strong capability). - Basic understanding of invoicing, AR aging, and month-end routines. Skills & Competencies - Solid Excel. - Detail-oriented, organized, and able to meet deadlines. - Strong communication; able to follow up professionally with internal teams and customers. - AI Tool power user/designer Preferred / Nice to Have - Exposure to ERP (SAP/Oracle/NetSuite/Dynamics) and/or ticketing tools (Jira/ServiceNow). - Power BI skill is preferred. - Exp
Senior AI Engineer
PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION We are looking for a Senior AI Engineer to help design and deliver agentic and generative AI systems that power R&D tooling for video game asset pipelines and production workflows. You will help shape the technical direction of our internal agent platform while building creative AI workflows that support artists, technical artists, and production teams. This is a senior, hands-on individual contributor role: you will write code, help design agentic architectures, build generative content pipelines, and partner with stakeholders across studios to turn emerging AI capabilities into production-grade tools. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Responsibilities Agent platform - Design and build key parts of our internal agent libraries - the core abstractions and developer ergonomics that let teams across the company build agents quickly and consistently. - Contribute to the architecture of our shared agent runtime and deployment patterns, helping teams run and maintain agents across production workflows. - Help define and evolve the agent loop / harness: prompt orchestration, tool invocation, sub-agent delegation, and recovery behavior. - Bring in reference patterns from the broader ecosystem, including open-source agent loops and harness projects, and adapt them to creative production use cases. Agent loop & harness engineering - Drive prompting and context strategy at scale: system prompt design, guardrails, mitigation of context poisoning and pollution, and management of context windows and model parameters. - Design tool interfaces for agents: MCP servers, structured inputs/outputs for context, and sub-agent composition patterns. - Advocate for typed-agent frameworks, clear debugging patterns, and practical tracing for non-deterministic workflows. - Evaluate and integrate hosted and local LLM options where latency, cost, quality, or data-residency requirements demand it. Creative AI workflows - Design, build, and maintain generative workflows for 2D assets, video, textures, concepts, and 3D-related content. - Evaluate and integrate image, video, multimodal, and 3D generation models for game-production use cases. - Develop and optimize node-based generation workflows using tools such as
Senior AI Data & Analytics Engineer
Support us in Agentic Analytics for a New Mobile Game! We're not looking for someone who has "built a dashboard". We're looking for someone who already uses agentic workflows as a core part of how they work: Claude Code, Codex, Cursor, custom agents, MCP servers, skills, planning loops, review gates, and AI-assisted engineering. Someone with strong opinions on which AI workflows hold up in production and which fall apart when real decisions depend on the numbers. You'll bring that practice to the AI-native analytics ecosystem of a brand-new mobile game. You'll define how gameplay, monetization, attribution, and player behavior data are collected, structured, and transformed into trustworthy insights, automated reporting, and AI-powered analytics tools. You will work at the intersection of AI, analytics, and game development, building the data foundation of a new game from scratch. You'll define its technical direction and drive the evolution of its analytics and AI capabilities from concept to production. Unlike a traditional analytics role, you'll use agents to dramatically increase your throughput while remaining the architect, reviewer, and final owner of correctness. The agents generate volume; you provide judgement. YOUR MISSION Build the Data Foundation - Design and operate the end-to-end gameplay analytics ecosystem. - Define tracking, storage, processing, and reporting architecture. - Own data correctness and make judgement calls when quality checks flag anomalies. Drive AI-Native Analytics - Build the semantic layer that translates raw gameplay data into validated gameplay and business concepts. - Develop AI-driven automated reporting, dashboards, and insight-generation workflows. - Evaluate and implement AI tools, agents, and workflows that improve analytics speed, reliability, and depth. - Review AI-generated code and analytics on critical paths before they reach production. Generate Product Intelligence - Identify opportunities, risks, anomalies, and trends across gameplay and player behavior. - Support product, balancing, design, and leadership teams with data-driven recommendations. - Translate complex datasets into clear, actionable insights. Set the Agentic Bar - Help define how the wider engineering organization adopts agentic practices. - Establish standards for tooling, review processes, quality gates, and what "done" means when agents generate most of the implementation. YOUR BACKSTORY - Several years of experience building analytics or data-driven systems in production environments, ideally in gaming or mobile. - Deep comfort with LLMs, agents, and AI-assisted engineering workflows in production environments. - Hands-on experience using agentic workflows and AI coding tools in real-world projects. - The ability to discuss concretely how you: - structure prompts and context, - manage autonomous and multi-agent workflows, including when to intervene, - use MCP servers, custom tools, skills, or subagents, - review AI-generated code and queries without becoming a bottleneck. - Strong experience working with behavioral, transactional, or event-based da
Technical Game Designer (AI Focus) - Fully Remote
SOFTGAMES is looking for an innovative Technical Game Designer with a passion for AI, game development, and workflow optimization. Your mission is not simply to build AI tools and pipeline optimization, but to create products that help game teams work faster, smarter, and more effectively. As one of the first AI-focused product specialists in our studio, you will identify production bottlenecks, design intuitive solutions, and drive the adoption of AI-powered workflows across multiple teams. You will work closely with game teams across the company, combining game design, AI, technology, and user experience to create solutions that make people’s work easier and more effective. We are not looking for someone who simply automates existing workflows. We are looking for someone who first improves and simplifies the way we work, and then leverages AI to amplify those improvements. *Qualified applicants will be expected to complete a test. Your Role: Drive the integration of AI tools and systems into game design, content creation, and production workflows across multiple projects. - Partner with designers, artists, producers, QA, analysts, and developers to identify bottlenecks, inefficiencies, and opportunities for improvement. - Challenge and improve existing workflows before introducing AI solutions. Focus on solving root causes, not simply automating existing processes. - Design and build intuitive AI-powered tools, automations, and workflows that deliver measurable value and are easy for teams to adopt. - Gather feedback, measure adoption, and continuously improve solutions based on real-world usage. - Inspire, educate, and mentor team members on AI best practices, tools, and emerging capabilities. - Evaluate new AI technologies and proactively identify practical opportunities to improve game development, content production, live operations, and internal workflows. - Create clear documentation, training materials, and best practices that enable teams to work more effectively. Your Profile: - 5+ years of experience in Game Design, Product Design, Technical Design, Product Management, Technical Art, or a similar role within gaming. - Strong product mindset with the ability to identify user problems, improve workflows, and drive adoption. - Experience designing tools, workflows, or systems used by both technical and non-technical users. - Strong understanding of UI/UX principles and user-centered design. - Excellent communication and stakeholder management skills, with the ability to collaborate effectively across multiple teams. - Proven ability to leverage AI to improve workflows, accelerate production, and solve real business problems. - Hands-on coding experience with Python, JavaScript, TypeScript, C#, C++, or similar languages, with the ability to rapidly prototype tools and workflows. - <span style="c
Software Engineer, Storage
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: Glean is seeking a Backend/Infrastructure Engineer to build and evolve the Storage layer that powers a highly available, performant, secure, and cost-effective suite of storage options for all data at Glean. - You’ll own the storage systems that handle Glean’s most sensitive data — from enterprise documents and permission hierarchies to user behavioral signals and real-time query path data. - Your work will directly enable organizations at scale to discover and act on their critical knowledge, supporting millions of searches, chat interactions, and agent workflows. - You’ll deliver robust uptime guarantees, autoscaling, and reliable alerting/monitoring for a key component that runs across multiple cloud providers. - As part of the Storage team, you’ll be responsible for a critical piece of Glean’s infrastructure, working closely with several other teams to support their workloads. - You’ll also work across the stack to abstract cloud differences, reduce human intervention through self-healing systems, and drive real business impact by enabling Glean’s ever-growing scale. You will: - Own impactful infrastructure problems from inception and architecture to production launch - Write well thought out design documents and robust, high-quality and well-tested code - Work collaboratively with a strong team to identify the most impactful projects we should be prioritizing in our roadmap - Mentor more junior engineers or learn from battle tested ones You are: - 5+ years of experience - BA/BS in computer science, or related degree - Experience working on infrastructure for distributed systems or cloud-native applications - Experience with storage systems (e.g., databases, object stores, or distributed file systems) Key knowledge and skills: - Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company is a must - A proactive and positive attitude to lead, learn, troubleshoot and take ownership of both small tasks and large features - Strong coding skills (for example in Go/Python/Java/C++ etc) with an emphasis on designing for reliability and scale, and writing well-tested components - Familiarity with cloud native development practices in GCP/AWS/Azure is a plus Location: - This role is hybrid (4 days a week in our Mountain View office) Compensation & Benefits: The standard base salary range for this position is $140,000 - $265,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Staff ML Engineer, Agent Training & Environments
Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: - Enterprise Platform & Tools : Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale - Frontier Data Labeling Service : Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models - Expert Marketplace : Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us - High-Impact Environment : We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. - Technical Excellence : Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. - Innovation at Speed : We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. - Continuous Growth : Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. - Clear Ownership : You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview Labelbox is the RL data factory for advancing frontier agent capabilities. We build the data, environments, and evaluations that frontier labs use to train and judge their agents. This role sits where training meets infrastructure. You will run the experiments and build the systems that run them: environments agents act in, verifiers that decide whether they succeeded, and the fine-tuning pipelines that turn that signal into a better model. We're looking for someone who does both halves — the engineering throughput of a strong platform engineer, and real depth in post-training agents. The bar is high: engineers with strong judgment who set technical direction, turn prototypes into reliable systems fast, and are at the frontier of agent-first engineering practice. What you'll work on - RL environments for agentic tasks: task definitions, tool surfaces, state and reset semantics, reward design — and the harness that runs thousands of them in parallel. - Verifiers and graders: programmatic checks, LLM judges, rubric pipelines, pass@k scoring. Deciding what "the agent succeeded" means, and making that judgment trustworthy at scale. - Fine-tuning pipelines that turn evaluation signals into measurable agent improvements — SFT and RL, from data collection through training to checkpoint evaluation. - Eval systems that run millions of agent trajectories to measure model and product quality. - Training and serving infrastructure that scales to the throughput frontier labs need: multi-launcher orchestration, long-running job fault tolerance, cost accounting. What we're looking for As an engineer - A 3+ year track record of shipping systems that customers and other engineers still rely on. - Exceptional throughput, without the quality tax. You ship a lot, you review a lot, and the v1 you ship becomes the foundation the rest of the team builds on. - Strong system and API design judgment. Hard architecture calls land with you: you make them, defend them under pressure, and update fast when someone else is right. - You ship production code with coding agents daily. You know where they break and what it takes to make them reliable, and you use that to move the whole team faster. - You build the substrate other people's work runs on — tooling, CI, harnesses, libraries — and you treat that as the job, not a distraction from it. - You move fast in ambiguous, startup-pace environments, with influence over authority. - Deep proficiency in Python, and comfort across the rest of the stack. As an RL post-training practitioner - You have fine-tuned models for agentic tasks and made them measurably better. SFT plus at least one RL method (GRPO, PPO, DPO, or similar) in production. - You have built environments agents operate in, and you know why reward and task design is where most of the difficulty actually lives. - You have designed verifiers or graders for open-ended work, and you know how they get gamed. - You debug training runs forensically and methodically. - You reason about compute-economics. You know what an experiment costs, when a run is not worth finishing, and how to get the same signal for a tenth of the spend. - You write up what you learned so it changes what the team does next. Nice to have - Experience with agent harnesses and coding agents as subjects of training and evaluation. - Multi-tenancy and isolation for untrusted agent execution: sandboxing, egress control, credential handling. - Background in production distributed systems, ML infrastructure, or data systems at scale. - Experience working directly with frontier labs or other highly technical customers. Our Technology Stack Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency: - Frontend: React.js with Redux, TypeScript - Backend: Node.js, TypeScript, Python, some Java & Kotlin - APIs: GraphQL - Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes - Databases: MySQL, Spanner, PostgreSQL - Queueing / Streaming: Kafka, PubSub Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location. Annual base salary range $250,000 - $280,000 USD Life at Labelbox - Environment : Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making - Growth : Career advancement opportunities directly tied to your impact - Vision : Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy : Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice . Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.
Senior Machine Learning Engineer, Public Sector
The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge .
Sr. Data Scientist
Position Summary, Responsibilities and Expectations: * Design, develop, and maintain machine learning models for use cases such as prediction, classification, and optimization * Build, optimize, and automate data pipelines using Python, PySpark, and SQL within Fabric and Snowflake environments * Perform exploratory data analysis (EDA) and feature engineering to improve model performance and interpretability * Deploy, monitor, and maintain production-level models to ensure scalability, reliability, and accuracy * Collaborate with business, product, and engineering teams to translate analytical insights into actionable solutions * Participate in AI and Large Language Model(LLM) initiatives, integrating language or generative models into workflows * Work with global, cross-functional teams across different time zones, requiring flexibility in working hours * Demonstrate a self-driven, proactive, and detail-oriented mindset, with strong ownership and adaptability in a fast-paced environment Essential Skills and Experience: * Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Finance, or a related field * Minimum 3+ years of hands-on experience in data science, analytics, or machine learning roles * Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and solid understanding of machine learning workflows * Experience with SQL and PySpark for large-scale data processing * Familiarity with modern data platforms such as Snowflake and Fabric * Experience with Git-based version control systems (e.g., GitHub or Bitbucket) * Knowledge of AI applications, including prompt-based systems and exposure to Large Language Models (LLMs) * Strong English communication skills, with the ability to collaborate effectively with global teams and present insights clearly * Ability to work flexible hours to support collaboration across different time zones This role is intended for a Mid-Senior Data Scientist, responsible for driving data-driven decision-making and improving operational efficiency through advanced analytics and machine learning techniques. The position involves designing and applying machine learning models on large-scale, global datasets, while contributing to scalable AI solutions, including emerging applications in artificial intelligence(AI) and large language models(LLMs). It also requires close collaboration with cross-functional, international teams to translate data insights into business value using modern data platforms and technologies.
AI Product Engineer
Madbox is a fast-growing mobile gaming company with a very unique way of developing games. Everything has been made for teams to take as much ownership as possible, unleash their creativity , bring performance , and have as much fun as possible. In July 2022, we launched our Pocket Champs game worldwide which quickly became one of the top-grossing games in its category. In our fast-paced, tech-driven environment, we continuously innovate by developing and updating our proprietary modules, along with integrating third-party ones, to enhance game functionalities, ensure precise analytics, and comply with evolving regulations. This dynamic ecosystem requires meticulous coordination to keep our games at the forefront of technology and user experience. Join Madbox to help shape how AI is integrated across our company, from developer productivity and internal tools to automation and data access. We are looking for a hands-on AI Product Engineer who can design, build, and scale AI-powered products and systems that teams use every day. This role combines software engineering, product thinking, technical leadership, and cross-team collaboration to accelerate how we build games and operate as a company. It also includes direct management of a web developer focused on AI-enabled internal tools. This role reports directly to the CTO and involves close daily collaboration with many stakeholders including teams of Game Tech, Data, Product and Web. Y our future responsibilities and scope: - Lead the design and implementation of AI-powered systems across the company - Build and maintain internal AI platforms, assistants, and automation tools - Integrate LLMs and AI capabilities into internal workflows and products - Collaborate with Engineering, Data, Product, and Operations teams to identify high-impact AI opportunities - Drive AI adoption and best practices across teams - Develop scalable AI architectures, APIs, and orchestration systems - Improve developer productivity through AI-assisted workflows and tooling - Define governance, reliability, and security standards for AI systems - Own AI platform cost management, usage monitoring, and pricing strategy to ensure scalable and sustainable adoption - Stay up to date with the AI ecosystem and continuously evaluate new tools, models, and approaches The profile we are looking for: - 5+ years strong software engineering background with experience building production systems - Proven experience working with modern AI technologies and LLM integrations - Hands-on experience with AI agents, orchestration frameworks, and RAG systems - Strong understanding of APIs, backend architectures, and scalable services - Experience integrating AI features into real products or internal platforms - Ability to translate business needs into practical AI solutions - Strong ownership mindset with the ability to drive initiatives independently - Comfortable collaborating across multiple teams and technical domains - Pragmatic approach focused on impact, usability, and execution - Strong communication skills and ability to explain AI concepts to both technical and non-technical stakeholders Please note: unfortunately, this position is not open to relocation and we cannot offer visa sponsorship. At Madbox, we value the mindset and how you can fit with our culture by sharing common values and creating great games together. We are passionate, always pushing to the next level to learn new things. We are creative and inn
AI Engineer
PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Responsibilities · Design, build, and deploy AI agents for operational workflows. · Integrate agents with enterprise systems (ERP, HRIS, SharePoint, Dynamics 365, Salesforce) via APIs, Power Automate, or Graph connectors. · Implement agent telemetry and observability pipelines using Microsoft Fabric or Power BI. · Apply RAG (Retrieval-Augmented Generation), context injection, and prompt-chaining for knowledge-aware automation if needed. · Maintain security, versioning, and audit trails for all agent deployments. · Perform exploratory data analysis (EDA) on Finance, HR, or current datasets to identify automation opportunities and trends. · Develop predictive ML models (e.g. anomaly detection, risk scoring). · Deploy ML models into Power BI or agents through Fabric ML endpoints, or Python scripts. · Collaborate with BI team to transform model output into decision-ready dashboards and alerts. · Continuously measure ROI and performance through agent telemetry and statistical evaluation. · Partner with the AI BA to translate business logic into model features and automation workflows. · Work with BI teams to ensure data readiness, integrity, and lineage. · Document models, pipelines, and prompts for auditability and reproducibility. Qualifications · Bachelor’s or Master’s degree in Computer Science, Data Science, or related field. · 4–8 years’ experience in data engineering, machine learning, or automation. · Strong proficiency in Python, SQL, and Power Platform (Power Automate, Copilot Studio, Power Apps). · Hands-on experience with EDA, regression/classification models, clustering, anomaly detection, and time-series forecasting. · Familiarity with Azure AI / Azure Machine Learning / Fabric ML environment. · Understanding of RAG pipelines, prompt-engineering, and LLM integration a plus. · Experience working with structured (ERP, Finance, HR) and semi-structured data (documents, logs). · Strong communication skills — can explain technical solutions to non-technical stakeholders. · Bonus: Exposure to Finance or Shared-Service operations preferred.
Data Science Tech Lead
BETER is a rapidly growing product company. We create competitive content supplemented with analytics. For more than 5 years, we have been organizing sports tournaments, broadcasts, and developing our own sports community. We hold 45,000+ events per month in esports and traditional sports, and our products are represented in 150+ countries worldwide. We are looking for a hands-on Data Science Tech Lead to join our team and drive the development of sports analytics and prediction products. This role combines deep technical expertise in machine learning and mathematical modeling with team orchestration and delivery ownership. You will work closely with the Engineering Manager and lead a team of 4 Data Science Engineers, helping transform business needs and production challenges into scalable data science solutions. Responsibilities: - Collaborate with the Engineering Manager to coordinate and support a team of 4 Data Science Engineers - Collect and analyze business requirements, production issues, and product needs, transforming them into actionable data science tasks and backlog - Analyze large volumes of sports, esports, and trading data - Develop and improve sports prediction models using statistics and machine learning techniques - Conduct, automate, and evaluate data-driven experiments - Integrate mathematical and ML models into production workflows - Participate in hands-on development and coding activities - Perform code reviews and maintain high engineering and data science quality standards - Ensure efficient execution and delivery of data science initiatives within the team Requirements: - Previous experience in a Tech Lead or team leadership role - Strong hands-on programming skills in Python - Advanced knowledge of databases and data processing - Strong expertise in machine learning, statistics, and probability theory - Experience building and deploying mathematical or predictive models - Upper-Intermediate+ level of English - Ability to balance technical leadership with hands-on engineering work What we’re looking for: This is primarily a hands-on engineering role. The main focus is building mathematical models, writing production-level code, and delivering real business impact through data science solutions. At the same time, the role requires strong coordination skills — the ability to distribute work effectively within the team, support engineers, and ensure successful delivery together with the Engineering Manager. Successful probation expectations: During the probation period, we expect the successful delivery of a sports analytics or modeling product through: - effective team orchestration, - hands-on contribution to development, - and high-quality execution of data science workflows. Ideal candidate profile: We would love to meet someone who is: - proactive in communication and information gathering, - focused on data-driven decision making, - detail-oriented and demanding when it comes to production quality and best practices. Also relevant: - High-load real-time data environments, such as fintech, gaming, marketing analytics, computer vision, or similar domains, working with large-scale data streams. We offer: - Ability to work remotely - Competitive and timely payment for services - Flexible work schedule - Personal mentoring and coaching - Team building and corporate events - 100% paid sick leave - 20 working days of paid vacation - Paid child care leave
Senior Software Engineer (ML/Game Development)
This is a hybrid position that requires residency in California, even during remote work periods. About the company: Located in Redondo Beach, CA, GungHo Online Entertainment America Inc. is the U.S. subsidiary of the Japanese game company GungHo Online Entertainment, Inc. Publishing titles across multiple platforms ranging from console to handheld and mobile, our group is comprised of veterans from various aspects of the industry brought together by one simple thing: a love of gaming. Position Summary: This position is responsible for owning the design, finetuning, and shipping of machine learning and generative AI features for our new, internally developed game, as well as setting technical direction and mentoring other engineers. You'll work at the intersection of applied ML and game development, and help define how AI shows up in our titles. What you’ll be doing: - Own the design, implementation, and debugging of ML/AI-driven features for our internally developed game, with a focus on LLM-powered NPC dialogue and model infrastructure. - Finetune, evaluate, and optimize models for in-game use, balancing quality against latency, memory, and cost. - Architect and maintain inference systems and data pipelines that integrate cleanly with the game engine and runtime. - Contribute to gameplay features and general game code alongside your ML work. This is a hands-on role on both sides. - Drive other generative AI features as the game evolves, scoping ambiguous problems into shippable work. - Partner with artists, game designers, and gameplay engineers to shape AI features, and help align them across teams. - Mentor engineers, review code and designs, and raise the technical bar of the team. - Test prototypes of future titles and AI systems to provide constructive feedback. - Attend industry conventions and live events as needed. Qualifications / desired experience: - Bachelor’s degree or equivalent in Computer Science or related technical discipline - 7+ years of video game development and product delivery experience is a plus - Significant professional experience building and shipping ML/AI systems, including finetuning or deploying models in production. - C++ and game-engine experience (Unreal) is a huge plus. - A track record of owning features end to end and making sound technical tradeoffs under real constraints (latency, memory, cost). - Solid general programming proficiency; deeply comfortable working in and improving a large production codebase. - No specific stack required. We care more about what you've actually built than which tools you used. - Experience deploying models for low-latency, real-time inference. - Experience mentoring engineers or leading technical direction on a team. - Familiarity with 3D graphics, shaders, or GPU programming is a plus. - Strong communication skills, including across disciplines. - Passion for narrative games. Why you want to work here: At GungHo, we’re enthusiastic about creating fun games and we’re always looking for talented individuals with whom we can share our passion. We have a highly collaborative culture where everyone wants to work together to get things done! Perks: - 100% employer-paid insurances: Health Insurance (PPO Medical, Dental, and Vision), Life Insurance, Accidental Death and Dismemberment insuranc
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