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At ControlExpert , a company of the Solvd Group based in Munich, you will be part of a team at the forefront on innovation in automotive claims management . Since our founding in 2002, we have been processing more than 20 million vehicle claims every year with over 1,200 employees worldwide. Our mission is to automate the claims settlement process by integrating advanced digital solutions and AI-supported tools to create a global platform for insurers. This platform acts as an end-to-end digital claim platform, delivering seamless and smooth customer experience. As experts in digitalization, we combine AI-driven processes and cutting-edge technologies with the deep expertise of our automative specialists . Together with our in-house research and development team , we are working to bring our vision to life: Car drivers all over the world will have their claims settled fairly on the very same day. Do you want to make an impact? Then become part of our team now! Work in our Data & AI Center of Excellence (DACE) in close collaboration with a diverse team of 45 data scientists and AI engineers from various disciplines Design and develop autonomous agent systems specifically tailored to the requirements of the insurance industry that independently analyze, plan and execute complex tasks – from architecture to production-ready deployment Develop and implement scalable AI products for the German and international market – from multi-agent systems to RAG and LLM pipelines to computer vision solutions – to optimize existing products or create completely new AI-powered solutions Research and test the latest AI processes , develop your own foundation models for the insurance industry and bring the most promising approaches into production – so that we as front runners will continue to be ahead of our competition in the future Qualification: Successfully completed studies in mathematics, (business) informatics, engineering, physics, data science and/or comparable training Wealth of experience & know-how: Ideally 5 years of professional experience, in-depth knowledge of the application of AI engineering methods with tools such as Python. Knowledge of machine learning, deep learning and especially in the field of generative AI, as well as experience in software development and data analysis as well as Focus on Agentic AI: Demonstrable experience, especially in the development of agent systems, RAG systems and LLM pipelines – from conception to production-ready implementation Personality & way of working: Initiative, way of working, analytical way of thinking and conceptual strength as well as the ability to present complex issues in an understandable way Nice-to-have: Experience as a data scientist in the insurance industry Language: Very good written and spoken English and Spanish skills , as well as ideally German language skills Want a quick overview of our benefits? Click hier! Work-life-balance: flexible working hours with ~80% remote work Fitness and wellness offers via Urban Sports Club Discounted Allianz products (insurance, pensions, investments) Bicycle leasing via JobRad Private leasing options for the latest tech devices Many employee events (sporting events, afterwork, parties, ...) Our in-house kitchen provides a delicious lunch at a fair price Corporate Benefits : Attractive discounts and voucher JBHU1_DE

At the BMW Group, everything starts with passion. It turns a profession into a vocation. It drives us to keep reinventing mobility and bring innovative ideas onto the roads. Enthusiasm for joint projects turns a team into a strong unit where every opinion is valued. It is only when expertise, highly professional processes and enjoyment of work unite that we can shape the future together. With our team of AI architects, AI engineers, and AI strategists, you will shape future system and hardware architecture, determine and drive software architecture with a strong focus on platforms, and design AI model architectures that interplay symbiotically. You design end-to-end AI and data architectures from data ingestion to model serving, using and extending platforms within our vehicles with a strong focus on edge computing. Furthermore, you build architectures that cover diverse use cases (e.g., automated driving, digital cockpits) to deliver holistic customer experiences. You provide architectural guardrails to business units and development teams, enabling competitive AI products on our AI platforms. Moreover, you drive the implementation of scalable AI software platforms, using the latest AI technologies and leveraging our in-house scalable software stacks. You link platform and application development by defining interfaces and ensuring that new requirements are integrated directly into the AI and data platforms. Master's or PhD in Computer Science, AI, Machine Learning, Data Science, or a related field, with over five years of experience in AI/data architecture. Experience in automotive E/E architecture and AI vehicle applications is a plus. Strong experience with vehicle AI architectures and implementation of Small Language Models, Vision Language Models, or autonomous driving models. Knowledge of multi-agent systems orchestration, multi-turn dialogues, and related open standards (e.g., A2A, MCP). Experience with AI training toolchains and workflows including pruning, fine-tuning, and multimodal encoding. Familiarity with open-source AI frameworks (LiteRT LM, ONNX GenAI, ExecuTorch, Llama-Stack) and comparison to proprietary frameworks. Skilled in Rust, C++, Kotlin, and API technologies. A profound understanding of AI models executed on hardware accelerators, with a focus on low-level software on Neural Processing Units (NPUs). Leadership experience in agile teams. Challenging projects with which we are shaping the mobility of tomorrow together. Wide range of personal and professional development opportunities. Attractive, fair and performance-related remuneration. High level of job security. Annual special payments such as vacation pay, Christmas bonus, and profit sharing. Flexible working hours including 6 weeks annual leave and overtime compensation. Discounted BMW & MINI conditions. Many other benefits at bmw.jobs/benefits Start date: from now on Type of employment: unlimited Working hours: FULLTIME At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants. Learn more here. JBHU1_DE

At the BMW Group, everything starts with passion. It turns a profession into a vocation. It drives us to keep reinventing mobility and bring innovative ideas onto the roads. Enthusiasm for joint projects turns a team into a strong unit where every opinion is valued. It is only when expertise, highly professional processes and enjoyment of work unite that we can shape the future together. As a Senior AI Platform Engineer, you will play a pivotal role in advancing the Data & AI transformation at the BMW Group by developing state-of-the-art AI platform solutions to train, run, and continuously improve tailored AI models for our connected vehicles all around the world. You build and operate AI platforms for data pipelines, training, deployment, and inference. You optimise for best-in-class AI models, employing suitable ML and LLM approaches. You take technical leadership and ownership, from architecture across teams to mentoring engineers towards operational excellence of AI-based systems. You analyse stakeholder requirements and translate them into scalable AI platform features that enable hundreds of teams. You ensure reliability, performance, and cost-efficient operation of AI-based systems. You develop solutions for efficient interoperability and load distribution between in-vehicle and cloud platforms. You create data and context management solutions to power personalised, customer-centric AI experiences. A university degree in Computer Science, Data Science, or a comparable qualification. At least five years of professional experience in (AI) platform engineering, AI training and inference, or AI tooling. A track record of successfully leading and implementing large and complex technical AI solutions in cloud or edge devices. Experience with AI solutions on the edge or enthusiasm to transfer your knowledge to the in-vehicle domain. Hands-on experience in machine learning or generative AI and proficiency in modern programming languages such as Python, Node.js/Nest.js, Java/Kotlin, or Go, as well as API technologies. A deep understanding of cloud architectures (mainly AWS), container orchestration (Docker, Kubernetes), and (ML)Ops of scalable cloud services. Very good written and spoken English skills. Knowledge of German, both written and spoken, is an advantage. Challenging projects through which we are shaping the mobility of tomorrow together. A wide range of personal and professional development opportunities. Attractive, fair, and performance-related remuneration. A high level of job security. Annual special payments such as holiday pay, Christmas bonus, and profit sharing. Flexible working hours including six weeks' annual leave and overtime compensation. Discounted BMW & MINI conditions. Many other benefits at bmw.jobs/benefits Start date: From now on Type of employment: Unlimited Working hours: Full-time At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruitment decisions are based on the personality, experience, and skills of the applicants. Learn more here. JBHU1_DE

Tieto is a leading software and digital engineering services company with global market reach and capabilities. We provide customers across different industries with mission-critical solutions through our specialized software businesses Tieto Caretech, Tieto Banktech and Tieto Indtech, as well as Tieto Tech Consulting business. Join our 15 000 talented vertical software, design, cloud and AI experts and empower our customers to succeed and innovate with the latest technology. Since 2000, Tieto has been represented in Germany. With about 100 experts, Tietoevry Germany is committed to develop enterprises and society through IT by realizing new opportunities in customers' business transformation. We believe in professional development and results by supporting our customers on their journey into a meaningful digital future Do you turn raw data into real impact? Do you see patterns where others see chaos, and opportunities where others see complexity? As a (Senior) Data & AI Engineer, you know that data is more than numbers - it's the foundation for smarter decisions and real business value. If you're driven by solving complex challenges, building scalable data solutions, and making an impact beyond the code, then you might be exactly who we're looking for. Tieto Tech Consulting is the leading digital accelerator for innovation and sustainable value creation. We combine business design with software engineering to bring digital business to life. With a team of around 300 highly qualified employees at our locations in DACH and a global team of 8,000 colleagues, we are constantly striving to develop and grow. Our customers trust in our solutions, which is why we are continuously looking for new talents. Design, build, and maintain scalable data platforms and data & AI solutions tailored to business needs, including the development of governance structures and access control concepts Design, implement and optimize robust data pipelines using modern frameworks such as Databricks or similar technologies Manage and enhance CI/CD pipelines for automated deployments, including containerization and orchestration Act as a trusted technical advisor and sparring partner for our customers Collaborate closely with cross-functional stakeholders to gather requirements and deliver impactful data-driven solutions Monitor, optimize and ensure the performance, scalability and reliability of data workflows Stay up to date with the latest trends in data engineering and apply innovative approaches to solve complex challenges 5+ years of experience in designing and implementing scalable data solutions, platforms, and data integration interfaces Strong expertise in data modeling (e.g. dimensional modeling, normalization/denormalization) Proven experience with cloud-based data platforms (Azure is preferred but experience with AWS or GCP is equally welcome) as well as tools like Databricks, Microsoft Fabric, and architectural patterns such as Medallion Strong programming skills in Python and SQL, with curiosity and openness towards leveraging AI-assisted stakeholders Solid software engineering mindset, including experience with Git, CI/CD pipelines and modern development practices Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders A consulting mindset with a customer-centric approach Fluency in German (C1 level) and English for stakeholder discussions Passion for emerging technologies and a continuous learning mindset in the evolving data & AI landscape developments and eager to learn about innovative IT solutions High level of ownership, self-motivation and the ability to quickly dive into new topics while constructively challenging the status quo As a person, we believe you are a team player who takes action and demonstrates responsibility to organize your work and solve your tasks. Within our agile, end-to-end development approach, you will both continuously learn from and actively mentor your colle

Do you want a job with a purpose? And do you want to make healthcare safer, better and more reliable? Join our Team! Join us as a AI Lead Product Manager - Data at Dedalus, one of the World's leading healthcare technology companies, based ideally in Milan, or in any of our European locations todo the best work of your career and make a profound impact in providing better care for a healthier planet. What you'll achieve As the AI Lead Product Manager you will own and drive the strategy and execution of our AI-powered Health Data Products portfolio. This is a senior leadership role spanning the full breadth of data focused products, from clinical and genomic data to operational and administrative data. It requires an individual who combines deep product expertise with the ability to build and inspire high-performing teams. The successful candidate will work with a team of Product Managers to set the product vision for each product, and provide senior-level leadership and mentorship to a team of product managers. This role demands both strategic thinking and hands-on product rigour, with a clear focus on delivering measurable value through AI-enabled data solutions for healthcare organisations globally. You will: Define and own the global product strategy and roadmap for AI-powered Health Data Products, spanning clinical, genomic, and operational data domains. Lead, develop, and grow a team of product managers, fostering a culture of ownership, collaboration, and continuous improvement. Engage with executive stakeholders across clinical, commercial, and technical functions to align on priorities and ensure product-market fit. Champion a data-driven approach to product decision-making, OKRs, and KPIs representing tangible impact measurement and value for our customers across the AI Data portfolio. Engage directly with healthcare customers and internal stakeholders to understand workflows, pain points, and opportunities for AI-driven improvement. Ensure each product within the Health Data product portfolio is supported by a business case. Support in the identification and evaluation of third-party solutions, AI vendors, and integration partners relevant to the HIS space, contributing to build vs. buy assessments. Ensure collaboration with the quality assurance team to ensure products comply with relevant regulatory, data privacy, and clinical safety requirements across target geographies (e.g. GDPR, HIPAA, HL7/FHIR standards). Communicate progress, risks, and strategic updates to the relevant stakeholders Oversee cross-portfolio dependencies and integration points across their portfolio and collaborating with the Leads for Health Information and Diagnostics product lines. Represent the health data product agenda within Dedalus and to our partners, customers Take the next step towards your dream career At Dedalus Life flows through our software . Every day we do something special by helping caregivers and health professionals deliver better care to their served communities. Take the next step in your career that will make a profound impact. Here's what you'll need to succeed: Essential Requirements: Bachelor's or Master's degree in a relevant field such as Health Informatics, Data Science, Computer Science, or Business. 5+ years of product management experience, with significant exposure to data-intensive AI products in healthcare or life sciences. Proven experience managing and mentoring product managers; demonstrated ability to build team capability and culture. Strong grasp of AI and machine learning concepts and their practical application to health data pipelines and analytics. Exceptional stakeholder management skills, with the ability to influence and align at all levels of the organisation across multiple geographies. Track record of defining and delivering complex, multi-domain product roadmaps from strategy through to execution. Strong understanding of healthcare data standards, governance frameworks, and privacy regulatio

Do you want a job with a purpose? And do you want to make healthcare safer, better and more reliable? Join our Team! Join us as a AI Programme Manager at Dedalus, one of the World's leading healthcare technology companies, based remotely in any of our European locations todo the best work of your career and make a profound impact in providing better care for a healthier planet. What you'll achieve As the AI Lead Product Manager you will coordinate and govern the delivery of AI initiatives across our global product portfolio, spanning Health Information Systems, Health Data Products, and Diagnostics. This role is central to ensuring that AI programmes are delivered on time, in scope, and in alignment with strategic objectives—bringing clarity, structure, and momentum to a fast-moving and complex landscape. You will: Own the coordination and governance of AI initiatives across the three focus areas—Health Information Systems, Health Data Products, and Diagnostics—ensuring alignment of milestones, dependencies, and priorities Establish and maintain programme-level planning artefacts including roadmaps, RAID logs, status dashboards, and milestone trackers across the AI portfolio Facilitate structured programme reviews and cross-functional forums, surfacing risks, decisions, and progress to the appropriate stakeholders Partner with Product Managers, Technical AI Lead, Quality Assurance, AI Compliance, and business stakeholders to ensure initiatives are well-scoped, resourced, and sequenced appropriately Ensure all product initiatives are KPI driven and follow the same standards and practices Identify and proactively manage cross-programme interdependencies, resource constraints, and delivery risks Engage and manage key stakeholders across the business around timelines, deliverables, queries and status of AI initiatives. Coordinate the creation of marketing materials across the product portfolio, working with the Lead PMs and Director of AI on the content Prepare and deliver executive-level programme reporting and communications, translating complex delivery landscapes into clear narratives Take the next step towards your dream career At Dedalus Life flows through our software . Every day we do something special by helping caregivers and health professionals deliver better care to their served communities. Take the next step in your career that will make a profound impact. The ideal candidate is a seasoned programme management professional who is comfortable navigating ambiguity in emerging technology environments, and who can build the cross-functional processes and stakeholder relationships needed to drive consistent delivery at scale. Here's what you'll need to succeed: Essential Requirements: 5+ years of programme or senior project management experience, ideally in technology, healthcare, or AI-driven product environments. Demonstrated experience managing portfolios of concurrent, interdependent technology initiatives at a global scale Strong understanding of AI product development cycles and the unique delivery challenges associated with data-intensive and ML-powered products Proficiency with programme management and collaboration tools (e.g. Jira, Confluence, Monday.com, Smartsheet) Excellent stakeholder communication and facilitation skills, with experience engaging senior and executive audiences Proven ability to build structure and drive progress in ambiguous, fast-evolving environments Native English speaker or C1/C2 English certification. Desirable Requirements: Relevant programme or project management certification (e.g. PMP, PgMP, PRINCE2 Practitioner, SAFe) Experience in the healthcare technology or health data industry Familiarity with agile delivery frameworks and experience operating in hybrid agile/waterfall environments Exposure to AI governance, responsible AI frameworks, or regulated software delivery environments Dedalus is committed to providing an engaging, rewarding work experience that reflects the passion

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Senior Forward Deployed Data Scientist/Engineer

Negotiable

At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment. This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability. The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions. What you’ll do - Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria - Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans - Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems - Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration - Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations - Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement - Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline - Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production - Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities What we’re looking for - 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role - Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact - Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans - Strong foundation in statistics, experimentation, causal reasoning, and measurement - Experience building tools or products, not just analyses — for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications - Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect d

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Prompt Engineer, Agent Prompts & Evals

Negotiable

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’re looking for prompt and context engineers to join our product engineering team to help build AI-first products, features, and evaluations. Your mission will be to bridge the gap between model capabilities and real product experience, working with product teams to build consistent, safe, and beneficial user experiences across all product surfaces. You will be deeply involved in new product feature and model releases at Anthropic, combining engineering expertise with an understanding of frontier AI applications and model quality. You’ll become an expert on Claude’s behavioral quirks and capabilities and apply that knowledge to deliver the best possible user experience across models and domains. You’ll be the first resource for product teams working on Claude’s AI infrastructure: system prompts, tool prompts, skills, and evaluations. This role requires someone who can effectively balance caring deeply about making Claude the best it can be while also supporting a wide variety of concurrent projects and efforts across many product teams. Key Responsibilities - Prompt Engineering Excellence: Design, test, and optimize system prompts and feature-specific prompts that shape Claude’s behavior across consumer and API products. - Evaluation Development: Build and maintain comprehensive evaluation suites that ensure model quality and consistency across product launches and updates. - Cross-functional Collaboration: Partner closely with product teams, research teams, and safeguards to ensure new features meet quality and safety standards. - Model Launch Support: Play a critical role in model releases, ensuring smooth rollouts and catching regressions before they impact users. - Infrastructure Contribution: Help build and improve the frameworks and tools that allow teams to develop and test prompts and features with confidence. - Knowledge Transfer: Mentor product engineers on prompt engineering best practices and help teams build their first evaluations. - Rapid Iteration: Work in a fast-paced environment where model capabilities advance daily, requiring quick adaptation and creative problem-solving. What We’re Looking For Required Qualifications - 5+ years of software engineering experience with Python or similar languages. - Demonstrated experience with LLMs and prompt engineering (through work, research, or significant personal projects). - Strong understanding of evaluation methodologies and metrics for AI systems. - Excellent written and verbal communication skills – you’ll need to explain complex model behaviors to diverse stakeholders. - Ability to manage multiple concurrent projects and prioritize effectively. - Experience with version control, CI/CD, and modern software development practices. &lt

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Privacy Research Engineer, Safeguards

Negotiable

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 looking for researchers to help mitigate the risks that come with building AI systems. One of these risks is the potential for models to interact with private user data. In this role, you'll design and implement privacy-preserving techniques, audit our current techniques, and set the direction for how Anthropic handles privacy more broadly. Responsibilities: - Lead our privacy analysis of frontier models, carefully auditing the use of data and ensuring safety throughout the process - Develop privacy-first training algorithms and techniques - Develop evaluation and auditing techniques to measure the privacy of training algorithms - Work with a small, senior team of engineers and researchers to enact a forward-looking privacy policy - Advocate on behalf of our users to ensure responsible handling of all data You may be a good fit if you have: - Experience working on privacy-preserving machine learning - A track record of shipping products and features inside a fast-moving environment - Strong coding skills in Python and familiarity with ML frameworks like PyTorch or JAX. - Deep familiarity with large language models, how they work, and how they are trained - Have experience working with privacy-preserving techniques (e.g., differential privacy and how it is different from k-anonymity, l-diversity, and t-closeness) - Experience supporting fast-paced startup engineering teams - Demonstrated success in bringing clarity and ownership to ambiguous technical problems - Proven ability to lead cross-functional security initiatives and navigate complex organizational dynamics Strong candidates may also: - Have published papers on the topic of privacy-preserving ML at top academic venues - Prior experience training large language models (e.g., collecting training datasets, pre-training models, post-training models via fine-tuning and RL, running evaluations on trained models) - Prior experience developing tooling to support privacy-preserving ML (e.g., differential privacy in TF-Privacy or Opacus) The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Job Title: Remote AI Video Data Contributor (LATAM & Caribbean) Job Type : Contractor | Remote Eligible Locations : Mexico, Costa Rica, Panama, Dominican Republic, Brazil, Argentina, Colombia, Chile, Uruguay, Jamaica, Bahamas, and Barbados. Application Deadline : May 22nd – 5 PM PST About the Role We’re looking for remote contributors to help support the development of next-generation AI and robotics systems through smartphone-based video and motion data collection. This is a flexible, paid remote opportunity where you’ll record simple real-world activities using your smartphone while following clear recording guidelines. No advanced technical background is required, but attention to detail and consistency are important. What You’ll Do Record short videos of physical activities using your smartphone Capture synchronized motion and video data during recording sessions Follow simple step-by-step recording instructions and quality guidelines Submit a minimum of 10 hours of approved video data per week Communicate with the team regarding recording quality or task instructions Complete a quick onboarding and device compatibility check Requirements Access to a compatible smartphone: iPhone 11 or newer Google Pixel 6 or newer Samsung Galaxy S21 or newer Ability to use a smartphone head strap for hands-free recording within 48 hours of onboarding Comfortable performing repetitive movement-based recording tasks Reliable internet connection and communication skills Strong attention to detail and ability to follow structured instructions Compensation Paid per minute of approved video submitted Compensation varies based on output and task completion speed Minimum submission requirements apply Videos must be at least 2 minutes long Weekly minimum submission target: 10 hours If you don’t already own a head strap, selected contributors will receive a sign-up bonus to help cover the cost. Why Join Fully remote and flexible Work from home using your smartphone Flexible schedule alongside studies or current work Fast onboarding process Contribute directly to AI and robotics development We move quickly and typically finalize onboarding within 48 hours for selected candidates.

Life is always about becoming… Becoming means going on a journey to be the best version of our future selves. While we discover new things, we will face challenges, master them and grow beyond our individual limits. Apply for a job at Mercedes-Benz and find your individual role and workspace to unleash your talents to the fullest. Empowered by visionary colleagues who share the same pioneering spirit. Joining us means becoming part of a global team that aims to build the most desirable cars in the world. Together for excellence. Job-ID: MER00042DZ Are you ready to drive the future of mobility with data and artificial intelligence? At Mercedes-Benz, we're not just building cars; we're crafting intelligent experiences and optimizing every facet of our operations with cutting-edge technology. We're seeking bright, ambitious university students to join our dynamic team as Data Analytics & AI Innovation Interns. In our functional area Finance & Controlling Standards, Solutions, Platform and Data / IT Group function, the Agile Release Train One Cost department designs and steers innovative solutions for planning, analysis, and reporting of costs and results in an international corporate environment. This is your chance to dive deep into real-world challenges, contribute to impactful projects, and shape the next generation of intelligent systems. If you have a passion for data, a knack for problem-solving, and an insatiable curiosity, we want to hear from you! What You'll Do: As an integral part of our team, you will: Engage in advanced Data Analytics to uncover insights and drive strategic decisions Work with state-of-the-art platforms like Microsoft Fabric to build robust data solutions and pipelines Explore and implement KI & Agent technologies, including AI-based Process Automation and sophisticated Agentic Flows Develop compelling Reports and Dashboards that transform complex data into clear, actionable visualizations Contribute to the development of AI-based Analytics and innovative Data Agents that enhance our capabilities Collaborate with cross-functional teams, applying your skills to projects that deliver real added value in data-driven decision-making Why our team @ Mercedes-Benz? This isn't just an internship; it's an opportunity to: Gain hands-on experience with cutting-edge technologies and real-world data challenges at a global leader in automotive innovation Receive mentorship from industry experts and grow your professional network Work in a collaborative, international, and highly motivated environment Contribute to shaping the future of mobility and making a tangible impact The activity can begin from October 2026. We are searching for proactive and talented individuals who possess: Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, Artificial Intelligence, Business Informatics, or a related quantitative field Strong analytical and technical skills, with a solid foundation in data manipulation and analysis Exceptional problem-solving capabilities and a creative approach to complex challenges A high degree of autodidactism, demonstrating a self-driven eagerness to learn new technologies and methodologies independently Proficiency in relevant programming languages (e.g. SQL) is a strong plus Familiarity with AI related topics and data visualization tools (e.g., Power BI) is beneficial A passion for data and using it to make sound data-driven business decisions Please note that your internship at this location must be mandatory. Ready to accelerate your career? If you're a curious mind with a drive for innovation and a desire to learn, we encourage you to apply! Join us and help define the future of intelligent driving. Additional Information: We look forward to receiving your online application, including a resume, cover letter, certificates, current certificate of enrollment stating your semester, proof of mandatory internship if applicable, and proof of the standard period of

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Research Engineer / Scientist, Societal Impacts

Negotiable

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 As a Research Engineer / Scientist on the Societal Impacts team, you'll design and build critical infrastructure that enables and accelerates foundational research into how our AI systems impact people and society. Your work will directly contribute to our research publications, policy campaigns, safety systems, and products. Our team combines rigorous empirical methods with creative technical approaches. We’re currently grappling with big questions on how AI might impact the future of work , people's wellbeing , education , and more. Additionally, we are continuously studying socio-technical alignment (what values do our systems have?), and evaluating novel AI capabilities as they arise. We develop privacy-preserving tools to measure AI's effects at scale, conduct mixed-methods studies of human-AI interaction, and translate research insights into actionable recommendations for both product and policy. You can learn more about our team here Strong candidates will have a track record of running & designing experiments relating to machine learning systems, building data processing pipelines, architecting & implementing high-quality internal infrastructure, working in a fast-paced startup environment, navigating the ambiguity inherent to novel empirical research, and demonstrating an eagerness to develop their own research & technical skills. The ideal candidate will enjoy a mixture of running experiments, developing new tools & evaluation suites, working cross-functionally across multiple research and product teams, and striving for beneficial & safe uses for AI. Responsibilities: - Design and implement scalable technical infrastructure that enables researchers to efficiently run experiments and evaluate AI systems. - Architect systems that can handle uncertain and changing requirements while maintaining high standards of reliability - Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions - Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission - Interface with and improve our internal technical infrastructure and tools - Generate net-new insights about the potential societal impact of systems being developed by Anthropic - Ship changes that help improve our models and products based on the empirical research the Societal Impacts team is conducting </li

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Software Engineer, Safeguards Labs

Negotiable

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 Safeguards Labs is a new team operating at the intersection of research and engineering, chartered to investigate novel safety methods that protect Claude and the people who use it. We prototype new approaches to safe models, usage safeguards, and production safety, pressure-testing ideas before they graduate into production systems run by our partner Safeguards teams. We're hiring software engineers to partner with our research engineers and turn promising prototypes into reliable, production-grade safeguards. The team is small, so each engineer has substantial latitude over what they work on and high leverage on the team's direction. Key responsibilities - Take research prototypes and harden them into production services that integrate with Anthropic's real-time safeguards path. - Build data and evaluation infrastructure that lets the team iterate on prototypes quickly and measure whether safeguards actually work, including in agentic settings. - Own deployment, monitoring, and reliability for systems Labs ships. - Build internal tooling that helps investigators surface and act on abuse patterns. - Collaborate with research engineers on scoping and contribute to decisions about which prototypes are ready to graduate. Minimum qualifications - Strong proficiency in Python and comfort working with large datasets. - A track record of designing, building, and operating production backend systems or data pipelines. - Experience taking software from prototype to production, including testing, monitoring, and reliability work. - Working familiarity with how large language models operate, even if LLMs aren't your primary background. - Care about the societal impacts of AI and want your work to directly reduce real-world harm. Preferred qualifications - At least 5 years of software engineering experience. - Experience deploying ML systems or classifiers into production. - Background in trust and safety, integrity, fraud detection, threat intelligence, or adversarial ML. - Experience building developer-facing tooling or platforms that accelerate research workflows. - Familiarity with evaluation methodologies for language models. - Experience with agentic environments. - A history of partnering with researchers and successfully transferring prototypes into production. The annual compensation range for this role is listed below. </p

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Manager, Machine Learning Research Scientist, GenA...

Negotiable

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. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed. As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery. You will: - Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments). - Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution. - Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes. - Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally. - Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent. - Stay deeply connected to the research community, understanding major trends, and helping set them. - Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results. Ideally you'd have: - 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains. - A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.). - Experience and track of recording in landing major research impacts in a fast-paced environment - Experience leading or managing research teams. You’re excited to mentor, coach and develop talent. - Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are

Start: Immediately | Level: Mid - Senior | Location: remote, Germany | Working Hours: Full Time (40h/week) Your next step in the Tech & Engineering team at ESN & More. As Staff Engineer (gn) - AI & Data Focus , you will help shape our architectural direction, strengthen our engineering foundations, and accelerate the responsible adoption of AI across teams. You work hands-on within your value stream while also contributing broadly across the organization - improving systems, enabling teams, and driving long-term technical impact. If you enjoy solving complex system challenges, mentoring engineers, and exploring pragmatic AI applications with measurable impact, this role is for you. To ensure smooth collaboration, we require a current primary residence in Germany for this position. Your mission You provide architectural and technical leadership by driving scalable architectures and long-term technical improvements across teams You support engineers hands-on in designing and implementing high-quality services, distributed systems, and data pipelines You collaborate closely with Product, Engineering, Data, and other Staff Engineers to align on architectural decisions and technical direction You evaluate and integrate AI technologies where they strengthen systems, processes, or product capabilities with measurable impact You enable responsible AI adoption by defining best practices, guidelines, and reusable patterns across engineering You mentor engineers and drive cross-team alignment while reducing complexity and improving engineering-wide consistency Your experience & skills You already work as a Staff Engineer and have impact on department level, not only within your team You have extensive experience in modern software engineering and distributed systems You bring strong architectural thinking and can align teams and stakeholders on technical decisions You have deep experience with event-driven systems, microservices, and AWS-based architectures You are familiar with data warehouse concepts, data modeling, data governance, data pipelines, and data quality frameworks You have a solid understanding of AI concepts such as LLMs, embeddings, vector search, agents, and automation patterns You have experience integrating AI capabilities into existing systems or workflows and assessing feasibility, risk, and impact You communicate fluently in English; German is a plus Why choose us? Being part of our team means joining a high-performing company with a strong and diverse culture. At TQG, you are not just a “super-senior engineer” – you are a force multiplier , influencing how our engineering organization builds systems, scales architecture, and adopts AI responsibly over time. You can expect meaningful technical ownership, broad organizational impact, and a collaborative environment that values clarity, pragmatism, and continuous learning. Additionally, you can look forward to: Flexible working hours and remote work options Attractive employee discounts Subsidy for the E-gym Wellpass Workation Corporate benefits 28 days vacation/year and much more About Us The Quality Group (TQG) is an innovative provider of sports nutrition products, bringing together the successful brands ESN and More Nutrition since 2021. ESN has been the German market leader in sports nutrition since 2004, offering products like protein powders, bars, and supplements designed for ambitious fitness goals. Founded in 2017, More Nutrition focuses on healthy, reduced-sugar foods, providing solutions for conscious nutrition and weight management without compromise. TQG's vision is to help people become the best version of themselves. With passion and innovation, the company develops high-quality products that promote health, performance, and joy in life. Its agile company culture and exciting career opportunities make TQG a strong partner not only for customers but also for employees. This is us – The Quality Group – nice to meet you! Now it's your turn! We look forwar

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Senior Machine Learning Engineer, Public Sector

Negotiable

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 . Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. You will: - Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers - Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics - Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines - Work with massive datasets to develop both generic models as well as fine tune models for specific products - Build scalable machine learning infrastructure to automate and optimize our ML services - Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations - Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment - Comfortable with light travel (approximately 10%) for customer interaction and team needs - This role will require an active security clearance or the ability to obtain a security clearance Ideally You’d Have: - Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment - Solid background in algorithms, data structures, and object-oriented programming - Strong programing skills in Python, experience in Tensorflow or PyTorch Nice to Haves: - Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization - Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments - Experience with computer vision, generative AI models, large language models, or agentic systems - Familiarity with ML evaluation frameworks and agentic model design

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Machine Learning Research Engineer, GenAI Applied...

Negotiable

About This Role Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes. Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research. If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you. You will: - Build and deploy multi-agent systems for agentic reasoning validation - Develop pipelines to detect errors and scale human judgment - Combine classical ML, LLMs, and multi-agent techniques for reliability - Lead research into agent failure modes and ship fixes - Use AI tools to speed prototyping and iteration - Build data-driven evaluations and deploy rapid improvements - Integrate systems into Scale's platform Ideally You’ll Have: - PhD or MSc in Computer Science, Mathematics, Statistics, or related field - 3+ years shipping scaled production ML systems - Demonstrated real-world impact - Mastery of PyTorch, TensorFlow, JAX, or scikit-learn - Deep expertise in agentic LLMs and multi-agent systems - Strong software engineering and microservices (AWS/GCP) - Rapid, data-driven iteration - Proficiency using AI tools to accelerate work - Strong research depth with practical bias - Excellent cross-functional communication Nice to Have: - Experience prototyping agent evaluation/reliability systems - Human-in-the-loop or annotation pipeline work - Open-source contributions in agents, evaluation, or alignment - Publications on agent reliability (NeurIPS, ICML, ICLR) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, th

PRODUCT DEVELOPER LIFESTYLE LABEL (M/W/D) Wir sorgen für den Wow-Effekt in der workwear-Welt. Echte Innovationen, Kleidung nach Maß, peppige Konzepte – mit unseren Produkten ziehen wir ganze Branchen an. Stillstehen ist nicht unser Ding. Wir sind immer in Bewegung. In unserer Branche gibt es viel Potential. Es warten neue Trends und clevere Technologien. Überzeuge dich selbst. Komm in unser „workwear-Valley“ nach Biebergemünd nahe Frankfurt a.M. und werde Teil von Europas führendem Hersteller von Arbeitskleidung. Bewirb dich jetzt. DEIN MENÜ: Du arbeitest als Product Developer eng im Team mit Design und Brand Partnern an der technischen Umsetzung und koordinierst den Entwicklungsprozess von der Prototyp-Entwicklung bis zur Marktreife. Als Produktentwickler bist du von Anfang an dabei und begleitest das Produkt hinsichtlich Passform und Verarbeitung. Auch kommunizierst und optimierst du in Zusammenarbeit mit Brand Partnern den Verarbeitungsprozess. Mit deinem Blick fürs Detail bist du verantwortlich für die gesamten technischen Produktionsunterlagen, wie Maßtabellen, Stücklisten oder Produktbeschreibungen. Du stellst sicher, dass alle Qualitäts- und Produktanforderungen in Bezug auf die neueste Technologie, Verarbeitung, Passform und Ausrüstung eingehalten werden. Du kannst innovative Lösungen zur Optimierung des Produktes beisteuern und diese umsetzen. DEINE ZUTATEN: Du hast eine abgeschlossene Ausbildung oder ein vergleichbares Studium im Bereich Bekleidungstechnik/-ingenieurwesen und konntest idealerweise mind. 3 Jahre Berufserfahrung in der technischen Produktentwicklung sammeln. Du besitzt Kenntnisse von Verarbeitungsprozessen, Materialien sowie auch von Passform- und Schnitterstellung. Du liebst es, angesagte Produkte in Zusammenarbeit mit Produktionsbetrieben (Europa/Asien/Mittelamerika) bis zur Marktreife zu begleiten und hast Spaß bei der Erstellung technischer Produktionsunterlagen, bei der du deine Erfahrungen mit modernen Verarbeitungstechniken einbringen kannst. Du bist ein Teamplayer mit einer strukturierten, selbstständigen sowie verantwortungsvollen Arbeitsweise und kannst dich flexibel auf neue Situationen einstellen, wobei dich dein Durchsetzungsvermögen sowie dein analytisches Denkvermögen auszeichnen. Du punktest mit deinen sehr guten Englisch-Kenntnissen in Wort und Schrift und bist fit im Umgang mit Adobe Illustrator sowie MS Office. UNSER ERFOLGSREZEPT: Wir Strausse setzen auf langfristige Beziehungen – auch bei unseren Arbeitsverträgen. Was bei uns auf den Tisch kommt, ist Champions League. Sagen jedenfalls die Experten - beste Kantine Deutschlands! Weiterentwicklung ist dir wichtig? Uns auch! Nutze unser Trainingsangebot. Beauty und Crema sind nicht alles. Aber Massage oder Meditation in der Mittagspause tun schon gut. Deine Gesundheit liegt Strauss am Herzen! Deshalb gibt's Strauss Care - von Physio über Medikamenten-Lieferservice bis betriebliche Altersvorsorge ist alles dabei. Ob Open Air BBQ an heißen Sommertagen oder legendäre Christmas Party – wir feiern unsere Gemeinschaft! Die Kleinen einfach morgens mit zur Arbeit bringen? Im Straussennest können sich die Meister von Morgen richtig austoben – und zwar ganztags. Top-Infrastruktur an der A66 On top: 30 Tage Urlaub, Urlaubs- und Weihnachtsgeld, Mitarbeiterrabatte Deine Daten kannst du uns schnell und einfach über unser Online-Formular unter "Jetzt bewerben" zukommen lassen. Du warst schon immer der „Streber-Typ“, dann schicke uns alles von dir zu. Eher der „Kreative-Typ“? Dann schicke uns das, was dir gerade vorliegt. Wenn wir noch etwas brauchen, kommen wir auf dich zu. Alternativ kannst du uns deine Bewerbungsunterlagen auch klassisch per Post zuschicken: Strauss GmbH & Co. KG HR - Human Relations Frankfurter Straße 98-108 63599 Biebergemünd, Deutschland Du hast Fragen? Schau gerne im FAQ nach oder melde dich bei: Tanja Herzberger 0 60 50 / 97 10 3003 hr@strauss.de

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Senior Product Manager, Agentic Science

Negotiable

Your work will change lives. Including your own. The Impact You’ll Make Recursion is leading an era of autonomous science – iterating across the discovery process, leveraging machine learning and agents built-for-purpose to uncover novel insights across biology and chemistry, fueling our clinical-stage pipeline. As the Senior Product Manager for Agentic Science, you will sit at the intersection of drug discovery and AI, serving as the critical translator between our scientific teams and the agentic systems they depend on. Your primary focus will be on outcomes: ensuring our agents impact Recursion’s pipeline through demonstrably accelerating discovery. This role is not about maintaining a static roadmap; it is about navigating the frontier of a rapidly evolving field. You will partner closely with drug discovery scientists to understand their workflows, translate their needs into agent task definitions, and design and maintain the benchmarks that -ensure our agents are driving value. As the field evolves rapidly, you will help the team distinguish real scientific progress from superficially promising results. In this role, you will: - Champion Benchmarking for Agentic Science: Drive alignment across scientific and technical teams around evaluation frameworks that measure agent performance against scientifically meaningful outcomes, continuously refining them as the field evolves. - Drive Outcome-Focused Product Development: Keep the team anchored to what matters: building agents that meaningfully advance drug discovery programs, not just executing tasks. - Evangelize the "Human-in-the-loop" Evolution: Work with scientific stakeholders to define interfaces where humans review, validate, and shape agent reasoning, ensuring our scientists evolve from "operators" to "architects" of discovery. - Monitor the Competitive Benchmark Landscape: Track how leading organizations across pharma AI, biotech, and foundation model research are measuring agentic performance. Ensure Recursion's evaluation frameworks stay calibrated against external standards, so our benchmarks reflect genuine scientific progress rather than internally optimized metrics. The Team You’ll Join You will join a cross-functional team of software engineers, data scientists, AI/ML scientists and drug discovery biologists and chemists who build the technical bedrock that enables autonomous science, including agent orchestration, guardrails, and the connectivity between our digital and physical assets. You will work closely with the Discovery teams (the users of these agents), the AI Research teams (who build cutting-edge models), and our automated biology and chemistry lab teams (who generate the data that feeds into the models). The Experience You’ll Need - Background in Drug Discovery or AI-driven Science: You have direct experience working in drug discovery, biotech, or AI-driven scientific research. Ideally, you will have worked hands-on with agentic systems (or agents) in a scientific context. You can credibly partner with PhD-level scientists and translate between scientific goals and technical systems without losing fidelity on either side. - Fluency

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Senior Research Scientist, Reward Models

Negotiable

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 As a Senior Research Scientist on our Reward Models team, you'll lead research efforts to improve how we specify and learn human preferences at scale. Your work will directly shape how our models understand and optimize for what humans actually want — enabling Claude to be more useful, more reliable, and better aligned with human values. This role focuses on pushing the frontier of reward modeling for large language models. You'll develop novel architectures and training methodologies for RLHF, research new approaches to LLM-based evaluation and grading (including rubric-based methods), and investigate techniques to identify and mitigate reward hacking. You'll collaborate closely with teams across Anthropic, including Finetuning, Alignment Science, and our broader research organization, to ensure your work translates into concrete improvements in both model capabilities and safety. We're looking for someone who can drive ambitious research agendas while also shipping practical improvements to production systems. You'll have the opportunity to work on some of the most important open problems in AI alignment, with access to frontier models and significant computational resources. Your work will directly advance the science of how we train AI systems to be both highly capable and safe. Note: For this role, we conduct all interviews in Python. Responsibilities - Lead research on novel reward model architectures and training approaches for RLHF - Develop and evaluate LLM-based grading and evaluation methods, including rubric-driven approaches that improve consistency and interpretability - Research techniques to detect, characterize, and mitigate reward hacking and specification gaming - Design experiments to understand reward model generalization, robustness, and failure modes - Collaborate with the Finetuning team to translate research insights into improvements for production training pipelines - Contribute to research publications, blog posts, and internal documentation - Mentor other researchers and help build institutional knowledge around reward modeling You may be a good fit if you - Have a track record of research contributions in reward modeling, RLHF, or closely related areas of machine learning - Have experience training and evaluating reward models for large language models - Are comfortable designing and running large-scale experiments with significant computational resources - Can work effectively across research and engineering, iterating quickly while maintaining scientific rigor - Enjoy collaborative research and can communicate complex ideas clearly to diverse audiences - Care deeply about building AI systems that are both highly capable and safe Strong candidates may also - Have published research on reward modeling, preference learning, or RLHF - Have experience with LLM-as-judge approaches, including calibration and reliabili

As a Fullstack Developer you work mainly with Java and React and you are working with experienced developers from all over Europe. We are building up a new office in Porto and you can take the chance to grow with us!

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Engineering Manager (AI Research & Model Training)

Negotiable

Perplexity is seeking a Research Engineering Manager to lead the team of all-star AI researchers and engineers responsible for developing the models that drive our products. Our team has developed some of the most advanced models for agentic research, query understanding, and other domains that require accuracy and depth. As we expand our userbase and portfolio of product surfaces, our in-house models are increasingly critical to providing a premium, high-taste experience for the world’s most sophisticated users. You will dive into our rich datasets of conversational and agentic queries, leveraging cutting‑edge training techniques to scale AI model performance. Through hands-on technical and organizational leadership, you will empower your team to develop SotA models for the use cases that matter most to our business and our users. RESPONSIBILITIES - Lead a team of researchers and engineers focused on training SotA models for Perplexity-relevant use cases, leveraging the latest supervised and reinforcement learning techniques. - Drive research and engineering efforts to develop production models through advanced model training and alignment techniques, including RL, SFT, and other approaches. - Become deeply familiar with the team’s technical stack, leading from the front through hands-on technical contributions. - Own the data, training, and eval pipelines required to train and continuously improve LLM models. - Design and iterate on model training and finetuning algorithms (e.g., preference‑based methods, reinforcement learning from human or AI feedback) through an approach that balances scientific rigor and iteration velocity. - Design evaluations and improve the production model training pipeline to reliably deliver models that lie on the Pareto frontier of speed and quality. - Work closely with engineering teams to integrate in-house models into our product and rapidly iterate based on real‑world usage. - Manage day‑to‑day execution, project planning, and prioritization for the model training team to hit ambitious quality and performance goals. QUALIFICATIONS - Proven experience with large-scale LLMs and Deep Learning systems. - Strong Python and PyTorch skills; versatility across languages and frameworks is a plus. - Experience leading or managing research or engineering teams working on large-scale AI model development, including driving complex projects from idea to production. - Self‑starter with a willingness to take ownership of tasks and navigate ambiguity in a fast‑moving environment. - Passion for tackling challenging problems in AI model quality, speed, safety, and reliability. - 10+ years of technical experience, with at least 2 of those years as a manager and at least 4 of those years working on large-scale AI model development. NICE-TO-HAVE - PhD in Machine Learning or related areas. - Experience training very large Transformer-based models with techniques such as SFT, DPO, GRPO, RLHF‑style methods, or related preference‑based optimization approaches. - Prior experience designing evaluations and production training pipelines for large‑scale models in a high‑growth environment.

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Deep Research Agent Tech Lead

Negotiable

Scale AI is seeking a highly technical and strategic Staff / Senior Staff Machine Learning Engineer to act as the Tech Lead (TL) for our next generation of deep research agents for the Enterprise. This high-impact role will drive the technical direction and oversight for Deep Research Agent Development , translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency. The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus. Responsibilities Technical Leadership & Vision - Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals. - Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities . - Core Agent Capabilities Development: - Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises. - Data analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas. - Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base. - Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale. - Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems. Team Leadership & Mentorship - Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth. - Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team. - Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent sol

Learn from experienced developers and work in an international new build team in our office in Porto. Join the subsidary at an early stage.

In this role, you will be reviewing online search results in order to improve their content and quality. You will be required to provide feedback and analysis on content found in search engine results and provide ratings on their relevance to the search terms used. Another aspect of this role will involve reviewing the language used in the search results by examining grammar, tone, and cultural relevance. You must have full professional proficiency in both written and verbal English & Irish You must be living in Ireland for the last 5 consecutive years You must own and use a Smartphone (Android V4.2 or higher or iPhone running iOS version 14.0 or higher) to complete tasks The majority of the task types will require both a desktop/laptop and a smartphone Gmail must be your primary email Active daily user of Gmail and other forms of social media You must have familiarity with current and historical business, media, sports, news, social media, and cultural affairs in Ireland Access to and use of a broadband internet connection and associated computer and software to perform the work, all provided at your own expense Experience in use of web browsers to navigate and interact with a variety of content

Help us developing software in our new office in Porto and work together with a lot of colleagues from all over Europe.

At mgm, we have been developing secure web applications for the commerce, insurance and public sector for over two decades and rely on model-driven software development with our enterprise low code platform A12. Our more than 850 colleagues at 17 international locations are united by a passion for digitalisation.

Online Data Analyst - German Speakers in Switzerland Job Description: Are you a detail-oriented individual with a passion for research and a good understanding of national and local geography? This freelance opportunity allows you to work at your own pace and from the comfort of your own home. A Day in the Life of an Online Data Analyst: In this role, you will be working on a project aimed at enhancing the content and quality of digital maps that are used by millions of people worldwide Completing research and evaluation tasks in a web-based environment such as verifying and comparing data, and determining the relevance and accuracy of information. Join us today and be part of a dynamic and innovative team that is making a difference in the world! TELUS Digital AI Community Our global AI Community is a vibrant network of 1 million+ contributors from diverse backgrounds who help our customers collect, enhance, train, translate, and localize content to build better AI models. Become part of our growing community and make an impact supporting the machine learning models of some of the world’s largest brands. Qualification Path: No previous professional experience is required to apply to this role, however, working on this project will require you to pass the basic requirements and go through a standard assessment process. This is a part-time long-term project and your work will be subject to our standard quality assurance checks during the term of this agreement. Basic Requirements Full Professional Proficiency in German and English Being a resident in Switzerland for the last 2 consecutive years and having familiarity with current and historical business, media, sport, news, social media, and cultural affairs in Switzerland Ability to follow guidelines and conduct online research using search engines, online maps, and website information Flexibility to work across a diverse set of task types, including maps, news, audio tasks, and relevance Daily access to a broadband internet connection, computer, and relevant software Assessment In order to be hired into the program, you’ll take an open book qualification exam that will determine your suitability for the position and complete ID verification. Our team will provide you with guidelines and learning materials before your qualification exam. You will be required to complete the exam in a specific timeframe but at your convenience. Equal Opportunity All qualified applicants will receive consideration for a contractual relationship without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. At TELUS Digital AI, we are proud to offer equal opportunities and are committed to creating a diverse and inclusive community. All aspects of selection are based on applicants’ qualifications, merits, competence, and performance without regard to any characteristic related to diversity.

As part of this role you will verify that business names and opening hours are correct. You will check that the distance from a starting point to an end destination is listed accurately, resulting in better user experiences. With this job you can plan your days around this highly flexible working schedule, work weekends or late evenings, all from the comfort of your own office . The flexibility of our roles minimizes the impact on your daily routine. So, whether you are a student looking to earn as you learn, a retiree looking for a new challenge, a part-time/full time professional or a work from home parent , Peroptyx has the right role for you! IdealCandidate: Fluent in English and Italian. Excellent research skills. Excellent local knowledge of your home country. Good understanding and general knowledge of the geography and culture of Italy. Analytical mindset. Must be living in Italy for a minimum of 5 consecutive years. Must pass an online open-book exam that can verify your full understanding of the material and concepts. Must be willing to work a minimum of 10 hours and up to 20 hours per week depending on task availability. Good working knowledge of search engines, map applications and familiarity with social media platforms. Strong ability to learn, understand and apply multiple sets of different instructions. All work must be of an independent nature. Work up to 20 hours per week. Earn a competitive rate of pay. Develop your research skills. Avoid the long commute. Work from the comfort of your home office. Enjoy the flexibility of setting your own working hou

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Senior Machine Learning Engineer, Discovery Recomm...

Negotiable

WHAT MAKES US EPIC? At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating. Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development. ANALYTICS What We Do Our Data & Analytics teams build powerful stories and visuals that inform the games we make, the technology we develop, and business decisions that drive Epic. What You'll Do You will design, build, and optimize the recommendation systems that power Fortnite's Discover experience, serving personalized recommendations to one of the largest player bases in gaming across a massive catalog of creator-built experiences. You'll work across the full recommendation stack: candidate generation, content ranking, impression allocation, and real-time reranking. Unlike recommendation systems that operate over a stable catalog, you're working with a massive, rapidly changing content library where new experiences are published daily, quality signals are sparse, and the system's own outputs shape the data it learns from. In this role, you will - Design and implement retrieval, ranking, and reranking models for creator content using deep learning approaches (two-tower architectures, transformer-based sequence models, embedding-based retrieval) and build the user representation systems that power personalized discovery - Build and optimize multi-stage candidate generation and impression allocation pipelines that balance relevance, diversity, and fair content exposure across a large and rapidly evolving catalog - Design and run A/B experiments to validate model improvements, own evaluation frameworks that capture recommendation quality holistically, and drive the path from experiment to production deployment - Collaborate with analytics and content quality teams on ranking signals including genre classification, creator credibility, and content quality metrics - Own ML infrastructure decisions: choosing the right tradeoffs between batch, near-real-time, and streaming serving architectures What we're looking for - 5+ years of experience building production recommendation or ranking systems, ideally in a UGC, marketplace, or content discovery context - Experience with deep learning for information retrieval and multi-stage recommendation pipelines (candidate generation, scoring, reranking) - Demonstrated ability to design and analyze A/B experiments, with awareness of biases inherent to recommendation systems - Strong Python engineering skills with experience in PyTorch and large-scale data processing frameworks (Spark preferred) - Comfort working in a cloud-based ML environment - Experience with explore/exploit strategies, content cold-start, or counterfactual evaluation methods applied to recommendation - Experience with content understanding models (NLP, vision, or generative AI) used as ranking features - Familiarity with creator economy dynamics and how recommendation design affects content quality and creator incentives - Exper

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Senior Machine Learning Engineer, Trust & Safety

Negotiable

Hinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role Join Hinge as a Senior Machine Learning Engineer, where you'll lead the application of AI and machine learning to effectively mitigate the impact of bad actors, remove policy violating content, and ensure user safety on the platform. Working closely with an expanding Trust & Safety team, you will collaborate with product managers, data scientists, engineers, and analysts to develop impactful AI/ML solutions. In this high-impact position within a small, dynamic team, you'll have the opportunity to play a foundational role in shaping how Hinge utilizes AI and machine learning in various contexts. Your expertise will be instrumental in creating a safer and more meaningful user experience on their journey to find an intimate connection. Responsibilities Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety. Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines. Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions. Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations. Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety. Stay abreast of new trends and research in AI/ML that can be applied to Trust & Safety initiatives to improve detection, user safety, and stay ahead of potential threats. What We're Looking For Strong programming skills: Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus . System design & architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference. Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features. Cloud and data platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus. Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives. Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds. Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation. Prior Experience 4+ years of experience

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Research Engineer / Scientist, Alignment Science -...

Negotiable

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: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy ), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team. Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas: - AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. - Alignment Stress-testing : Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London and travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python. Representative Projects: - Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions. - Run multi-agent reinforcement learning experiments to test out techniques like AI Debate . &lt

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Product Manager of AI Applications, Global Public...

Negotiable

Scale is growing rapidly, and joining the Global Public Sector team is an opportunity to work on one of the most exciting and quickly expanding teams at Scale. This team is responsible for generating, executing, and fostering Scale’s work with governments and government-backed entities outside of the United States. We develop bespoke solutions that leverage our customers’ proprietary data and expertise to transform their organizations with AI. We work with them to understand their pain points and workflows and then forward deploy our team to build cutting-edge solutions. The applications we build are powered by the Scale GenAI Platform, a full stack product to build, test and deploy frontier AI agents. - Developing custom AI applications - Building custom LLMs - Providing high-quality training data for research and government institutions building LLMs - Developing partnerships to foster regional talent growth and AI adoption We are looking for an entrepreneurial and experienced product leader to play a pivotal role in the ideation and development of transformative AI solutions. The ideal candidate has deep experience with AI/ML application development, can think strategically about how to solve a problem, is an excellent listener, is comfortable getting into the weeds operationally, and has a strong understanding of software engineering principles and practices. You will be responsible for owning large AI projects for one or many customers. You will lead a cross-functional team of engineers, MLEs, and operators to build a highly impactful solution for our customers that will drive millions in revenue for our business as well. Responsibilities: - Lead design workshops with the client to define custom AI solutions - Scope out new AI application use cases across various government entities - Lead cross-functional development of AI applications and custom LLMs with diverse stakeholders (Engineering + Ops + Go-to-Market) - Consistently engage with future end-users to solicit feedback and ensure we are prioritizing effectively - Stay up to date with latest research in applied AI and training custom LLMs - Scope out model evaluation sets and performance requirements, consistently review results, and iterate on the solution - Give regular progress updates to the client and Global Public Sector leadership Minimum Qualifications: - 4+ years of experience building products with specific experience within the last 1-2 years building AI-powered products - Strong technical background (STEM degree) and/or experience building technical software products - Strong understanding of generative AI technologies and their applications in both enterprise and consumer settings - Experience with vibe coding tools (i.e., Replit, Lovable, Bolt, etc.) and design tools (i.e., Figma/Canva/Miro) - Exceptional leadership, presentation and communication skills with the ability to influence cross-functional teams Nice to haves: - Coding experience (Python) - Proficiency in Arabic, both written and spoken PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all ap

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Research Engineer/Research Scientist, Audio

Negotiable

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. Anthropic’s Audio team pushes the boundaries of what's possible with audio with large language models. We care about making safe, steerable, reliable systems that can understand and generate speech and audio, prioritizing not only naturalness but also steerability and robustness. As a researcher on the Audio team, you'll work across the full stack of audio ML, developing audio codecs and representations, sourcing and synthesizing high quality audio data, training large-scale speech language models and large audio diffusion models, and developing novel architectures for incorporating continuous signals into LLMs. Our team focuses primarily but not exclusively on speech, building advanced steerable systems spanning end-to-end conversational systems, speech and audio understanding models, and speech synthesis capabilities. The team works closely with many collaborators across pretraining, finetuning, reinforcement learning, production inference, and product to get advanced audio technologies from early research to high impact real-world deployments. You may be a good fit if you: - Have hands-on experience with training audio models, whether that's conversational speech-to-speech, speech translation, speech recognition, text-to-speech, diarization, codecs, or generative audio models - Genuinely enjoy both research and engineering work, and you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other - Are comfortable working across abstraction levels, from signal processing fundamentals to large-scale model training and inference optimization - Have deep expertise with JAX, PyTorch, or large-scale distributed training, and can debug performance issues across the full stack - Thrive in fast-moving environments where the most important problem might shift as we learn more about what works - Communicate clearly and collaborate effectively; audio touches many parts of our systems, so you'll work closely with teams across the company - Are passionate about building conversational AI that feels natural, steerable, and safe - Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly Strong candidates may also have experience with: - Large language model pretraining and finetuning - Training diffusion models for image and audio generation - Reinforcement learning for large language models and diffusion models - End-to-end system optimization, from performance benchmarking to kernel optimization - GPUs, Kubernetes, PyTorch, or distributed training infrastructure Representative projects: - Training state-of-the art neural audio codecs for 48 kHz stereo audio - Developing novel algorithms for diffusion pretraining and reinforcement learning - Scaling audio datasets to millions of hours of high quality audio - Creating robust evaluation methodologies for hard-to-measure qualities such as naturalness or expressivene

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Senior/Staff Machine Learning Engineer, General Ag...

Negotiable

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: - Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. - Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. - Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. - Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. - Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems. - Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage. - Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level. Ideally you’d have: - 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases. - Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience. - Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design. - Proven proficiency in Python, including writing production-quality, testable, and maintainable code. - Experience building systems that integrate models with external tools, APIs, databases, and services. - Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints. - Strong communication skills and comfort working in customer-facing or cross-functional environments. Nice-to-haves: - Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs). <li&g

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Staff Machine Learning Research Engineer, Agent Po...

Negotiable

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As a Staff Agent Post-Training MLRE, you will build out our next-gen Agent RL training platform. You’ll build out the platform that will train best-in-class Agents that achieve state of the art results on real enterprise use-cases. You’ll integrate cutting edge research into our training stack, enabling MLREs on the Enterprise AI team to deploy use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you! You will: - Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. - Research cutting edge algorithms to integrate directly into our training stack. - Design solutions that enable complex multi-agent systems to directly learn from both process + outcome based rewards. Ideally you’d have: - 5+ years of LLM training in a production environment - Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. - Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years - PhD or Masters in Computer Science or a related field Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $250,000 - $350,000 USD <div class="content-conclusion"&gt

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Research Engineer, Machine Learning (Reinforcement...

Negotiable

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 teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation. Representative projects: - Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters. Help scale our systems to handle increasingly complex research workflows. - Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models. - Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows. - Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research. You may be a good fit if you: - Are proficient in Python and async/concurrent programming with frameworks like Trio - Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX) - Have industry experience in machine learning research - Can balance research exploration with engineering implementation&lt

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Machine Learning Research Engineer, Agent Data Fou...

Negotiable

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As MLRE on the Data Foundation team, you’ll work on cutting edge research to define the data flywheel that makes the whole machine move. This includes research around synthetic environments from task definitions, building agents for trace analysis, and contributing to a cutting edge framework that automatically hill-climbs agent-building from an eval set. This will involve creating best-in-class Agents that achieve state of the art results through a combination of post-training + agent-building algorithms. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you! You will: - Build synthetic data pipelines to generate enterprise environments to use for RL post-training - Create agents to convert traces from production into actionable insights to use to improve agents - Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms - Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. Ideally you’d have: - 3+ years of building with LLMs in a production environment - Clear experiences with constructing high quality data to use to improve an LLM/Agent - Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years - PhD or Masters in Computer Science or a related field Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $250,000

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GenAI Strategic Projects Lead, Public Sector

Negotiable

Scale is at the frontier of the AI industry, improving the world’s leading generative AI and large language models through model evaluations, human-powered supervised fine-tuning datasets, world-class reinforcement learning with human feedback, and more. Scale AI’s Public Sector team is growing in the Generative AI space, and we’re seeking an Strategic Projects Lead to own high-impact projects that drive revenue and experimentation. In this role, you’ll work across operations, engineering, and customer engagement to produce world-class training and test and evaluation data for Large Language Models for our Public Sector customers. This role offers a rare opportunity to make a meaningful impact at the intersection of AI and national security. You will help build Generative AI data-labeling pipelines from the ground up, create operational processes to manage and optimize an in-house expert data workforce, and develop novel technology-driven approaches (e.g., scripts, prompt engineering, hybrid data) to improve the quality of our training and evaluation datasets. In addition, you will partner directly with our internal machine learning experts and external stakeholders to ensure our data enables the development of mission-critical applications of AI. You will: - Develop, build, and maintain the infrastructure required to ensure data pipelines are efficient, scalable, and produce high-quality outputs - Take ownership of day-to-day progress on high-priority data production pipelines, ensuring projects move forward efficiently - Partner with subject matter experts in their fields to validate the quality of our data and to translate deep domain knowledge into scalable processes and measurable outcomes - Work closely with customers to understand their requirements and design data taxonomies that optimize model performance. - Utilize analytics and data visualization tools to track progress, identify bottlenecks, and make data-driven decisions to optimize pipeline performance - Influence cross-org collaboration to define and advance human data strategy, influencing technical and non-technical stakeholders to ensure data quality, scalability, and long-term platform leverage - Own larger and larger components of our data delivery processes, until you ultimately serve as the full owner of our most visible and high impact customer pipelines You have: - 5+ years of experience in product development, data science, or operations - A history of successful project management and comfort in ambiguity - Ability to analyze complex operational data, build queries, and identify trends to inform decisions and optimize processes - Technical aptitude to understand how to produce data for state of the art post-training techniques such as supervised fine tuning (SFT), reinforcement learning through human feedback (RLHF), Reinforcement Learning with Verifiable Rewards (RLVR) etc Nice to have: - Experience working in defense tech and/or an AI company - A technical degree in fields like computer science, data science, or engineering - A deep understanding of ML operations for generative AI workflows / products - An active Top Secret security clearance <div class="content-pay-transparenc

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Machine Learning Systems Research Engineer, Agent...

Negotiable

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. As an ML Sys Research Engineer, you’ll work on building out the algorithms for our next-gen Agent RL training platform, support large scale training, and research and integrate state-of-the-art technologies to optimize our ML system. Your customer will be other MLREs and AAIs on the Enterprise AI team who are taking the training algorithms and applying them to client use-cases... Observed freshness date: 2026-08-04T01:04:41-04:00 Freshness signal: first_party_updated_at Remote signal: unknown Salary: not published Canonical apply URL: https://job-boards.greenhouse.io/scaleai/jobs/4625341005 Source URL: https://job-boards.greenhouse.io/scaleai

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Research Engineer, Production Model Post-Training

Negotiable

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

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Senior Technical Designer (AI Design)

Negotiable

Senior Technical Designer (AI Design) at Crytek GmbH. German games industry role. Company category: Developer. Job category: Game / Level Design. Job type: Full-Time. Added: 18.01.2026.

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AI Engineer

Negotiable

As an AI Engineer at Cloud Chamber you will join our talented development team to further push the development of the AI Systems and AI Archetypes for BioShock 4. We have high ambitions for tying AI and storytelling together in our project. It will be your responsibility to support several AI Systems and bring our AI Archetypes to life. In this role, you’ll help push the state of the art, and experiment with unproven ideas. We are attempting new and ambitious things with AI in this game. You are a bold and curious engineer who believes in an iterative, experimental approach to game development; moving comfortably between design and engineering, collaborating and communicating ambition and limitations. What You’ll Do: - Collaborate with the engineering and design teams to iterate and polish existing AI Systems and Archetypes. - Support the development of architecture and implementation within the systems of your domain. - Collaborate with other engineers to implement and maintain AI behavior trees and associated systems. - Test our AI Systems and Archetypes, reporting on their performance operation and memory budgets. - Test and suggest improvements for combat design-facing authoring and encounter scripting tools for - Maintain technical documentation. What We’ll Do Together: You will work closely with our Design, Animation, Audio, VFX, and Art departments to support and finalize the implementations for core AI systems: Combat Management, Perception, Steaming/Memory/Performance, etc. You will also help support the creation of new AI Archetypes and finalize existing ones. You will be encouraged to push our conception of what is possible, doing as much to advance the ambition as you will attempt to build it, ultimately bringing our richly imagined world to life. &lt

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AI Engineer

Negotiable

As an AI Engineer at Cloud Chamber you will join our talented development team to further push the development of the AI Systems and AI Archetypes for BioShock 4. We have high ambitions for tying AI and storytelling together in our project. It will be your responsibility to support several AI Systems and bring our AI Archetypes to life. In this role, you’ll help push the state of the art, and experiment with unproven ideas. We are attempting new and ambitious things with AI in this game. You are a bold and curious engineer who believes in an iterative, experimental approach to game development; moving comfortably between design and engineering, collaborating and communicating ambition and limitations. What You’ll Do: - Collaborate with the engineering and design teams to iterate and polish existing AI Systems and Archetypes. - Support the development of architecture and implementation within the systems of your domain. - Collaborate with other engineers to implement and maintain AI behavior trees and associated systems. - Test our AI Systems and Archetypes, reporting on their performance operation and memory budgets. - Test and suggest improvements for combat design-facing authoring and encounter scripting tools for - Maintain technical documentation. What We’ll Do Together: You will work closely with our Design, Animation, Audio, VFX, and Art departments to support and finalize the implementations for core AI systems: Combat Management, Perception, Steaming/Memory/Performance, etc. You will also help support the creation of new AI Archetypes and finalize existing ones. You will be encouraged to push our conception of what is possible, doing as much to advance the ambition as you will attempt to build it, ultimately bringing our richly imagined world to life. &lt

CTO (Unity Game Developer + AI agents) at Lake System. German games industry role. Company category: Developer. Job category: Tech / Programming. Job type: Full-Time. Added: 30.05.2026.

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Senior Computational Biologist – Target ID

Negotiable

Your work will change lives. Including your own. The Impact You’ll Make As a computational biology specialist on our Target ID team, you will be at the forefront of transitioning Recursion to its next era of drug discovery. You will serve as a critical biological anchor for a highly technical data science team building the next generation of our target discovery pipelines. The team’s mission is to identify novel therapeutic targets at scale across the genome for hundreds of indications. You will have access to all of Recursion's data layers—including massive internal maps, functional genomics, and rich patient data (transcriptomics, genetics, and Real-World Data/EHR)—and will be tasked with proposing, piloting, and deploying new methods to integrate these datasets. Crucially, you will leverage your biological subject matter expertise to orient and focus your data scientist and software engineer peers towards reliable and correct usage of biological data and feasible candidate programs. As we build out semi-automated and agentic tools (e.g., multi-agent LLM systems for portfolio oversight and target assessment), your deep real-world biology experience will guide the development of these tools, ensuring they are grounded in biological reality and translate to meaningful portfolio and patient impact. The ideal candidate is a computational biology specialist with high fluency in data science tech stacks. You know how to build and evaluate predictive models and build agentic pipelines, and your differentiator is your deep understanding of patient-relevant datasets, disease biology, and target discovery. In this role, you will: - Discover & Evaluate: Propose and validate novel targets using deep integration of patient data (transcriptomics, population genetics, EHR, etc) and Recursion's internal multi-omic data layers. - Guide & Automate: Collaborate closely with data scientists to build, refine, and guide semi-automated and agentic target discovery tools. You will ensure these tools are biologically sound and can scale to evaluate hypotheses across many indications spanning a wide range of therapeutic areas. - Triangulate: Use advanced statistical methods (e.g., causal inference, survival modeling) to establish confident target-to-patient connections and define specific addressable patient populations for early pipeline programs. - Bridge the Gap: Translate complex platform findings into disease-relevant applications, bridging the gap between high-dimensional data science output and actionable drug discovery insights. - Present & Influence: Communicate complex biological rationale and data analyses to decision-makers and cross-functional stakeholders, driving data-backed "go/no-go" decisions in a two-stage target approval process. The Team You’ll Join Our group is a bold, agile, diverse collective of data scientists and computational biologists driving Recursion’s early portfolio strategy. We are focused on aggressively expanding our early-stage pipeline with highly validated, novel therapeutic targets. To achieve this, we prioritize defining specific patient populations and establishing clear, data-backed translational paths from day one of every new program. Because this

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AI Rust Engineer

Negotiable

Software development is becoming a collaboration between developers and AI systems. Most AI developer tools operate on prompts and static snapshots of code. But real software development happens inside large, evolving codebases that change continuously through edits, refactors, discussions, and collaboration. We are building AI systems that operate inside that environment. Zed today is a code editor built from scratch in Rust with GPU acceleration and real-time multiplayer collaboration. Every keystroke and edit can be shared instantly between collaborators, creating a shared workspace where developers and increasingly AI systems can work together. We are also building DeltaDB https://zed.dev/blog/sequoia-backs-zed, a system that records the operational history of software development. It captures edits, discussions, and AI interactions as they happen. This creates a foundation for AI systems that can reason not just about code, but about how that code evolves over time. Much of this work involves designing systems that help AI understand large, evolving codebases. This includes providing the right context and evaluating whether its suggestions actually improve the software. The work sits at the intersection of AI systems, developer tools, and distributed collaboration. We are exploring how software gets built when AI becomes part of the development environment itself. SOME QUESTIONS WE ARE EXPLORING Many of these questions do not yet have established answers. Part of the work is designing and testing new approaches in real developer workflows. - How should AI reason about codebases that are constantly evolving rather than static repositories? - How can streams of development activity such as edits, refactors, and discussions provide useful context for models? - What does it mean for AI to operate inside a real-time collaborative environment where multiple developers are editing the same project? - How should AI systems make suggestions without interrupting developer flow? - How do we evaluate whether AI systems are genuinely helping developers understand and evolve complex software systems? WHAT YOU WILL WORK ON - Designing systems that allow AI to participate directly in developer workflows - Building infrastructure that connects language models with the editor and developer tools - Developing context systems that help models reason about large codebases - Designing evaluation frameworks for AI-assisted development - Improving the reliability, latency, and cost efficiency of AI features - Working closely with editor and infrastructure engineers to ship ideas quickly - Pair programming with teammates to explore ideas and refine systems together REQUIREMENTS - Experience building production systems powered by large language models - Strong understanding of model behavior, prompting, and evaluation - Experience integrating AI capabilities into real software products - Strong backend or systems programming experience - Interest in developer tools and programming environments - Ability to collaborate closely with other engineers - Experience with Rust, or willingness to learn PREFERRED EXPERIENCE - Building AI coding assistants or developer tools - Designing evaluation systems for LLM-driven products - Working with large codebases, compilers, or programming environments - Experience with tool-using or agent-style models - Experience with Rust ABOUT ZED Zed is open source and built in public by the team behind Atom and Tree-sitter. The editor is written in Rust with GPU acceleration for every frame. When you type or move the cursor, pixels respond instantly. That responsiveness keeps you in flow. Zed is multiplayer by default, allowing developers to work together in the same codebase in real time. Much of our work happens through pair programming, with engineers collaborating directly inside the editor. We ship improvements weekly and work closely with a community that cares deeply about the craft of developer tools. Location: Rem

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AI Research Engineer - Datadog AI Research (DAIR)

Negotiable

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: - World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. - Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: - Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling - Implement models, run experiments at scale, and profile for reliability, performance, and cost - Build simulation environments and replay infrastructure for agent training and evaluation - Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery - Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity - Collaborate with Research Scientists, Product, and Engineering to integrate capabilities into Datadog's products and to harden prototypes into reliable services - Contribute to research publications at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and produce high-quality code, documentation, and open-source artifacts Who You Are: - You have depth in distributed computing, RL Infra, and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus - You are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and comfortable with modern cloud and data infrastructure - You have practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU acceleration - You have practical experience with large-scale model training and fine-tuning, including