RLHF Jobs

OpenAI

We are seeking a researcher to train and evaluate models for U.S. government use, with a focus on national security applications. You will advance safety post-training and robustness, helping models follow nuanced policies while preserving their usefulness and capabilities. This role involves researching and implementing methods for safety training, reinforcement learning, and adversarial robustness, as well as developing evaluations, identifying model failure modes, and using findings to improve training. You will also collaborate with research, engineering, security, and policy partners to support safe, reliable deployment.

Fireworks is seeking an Applied Machine Learning Engineer for the EMEA region. In this role, you will be the technical owner of customer engagements, embedding within client teams to understand their specific needs and challenges. You will be responsible for the entire lifecycle of a customer's deployment on the Fireworks platform, from initial scoping and model selection to ensuring production readiness, performance, and cost-efficiency. This position emphasizes first principles thinking and requires a deep understanding of software engineering, machine learning techniques, and infrastructure optimization.

Anthropic

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.

Anthropic

Anthropic's RL Data Platform team is responsible for building the systems that generate, process, and serve the human data used to train Claude. This involves creating interfaces for human feedback, developing pipelines to transform raw feedback into training signals, and providing tools for researchers to launch, monitor, and analyze data collection efforts. The team ensures a consistent supply of high-quality data, enabling researchers to collect new data types rapidly and integrate them into the training process. This is a full-stack, ownership-driven role on a senior team, requiring the engineer to design and implement web interfaces for annotators, build backend services and data pipelines, and collaborate closely with RL researchers to define and fulfill data requirements. The role emphasizes building for reliability, treating researchers as users, and ensuring the quality of the data produced.

Anthropic

Anthropic's RL Data Platform team is responsible for building and maintaining the systems that generate, process, and serve the human data used to train Claude. This involves creating interfaces for human feedback, developing pipelines to transform raw feedback into training signals, and providing tooling for researchers to manage data collection. The role is full-stack and requires ownership of projects from conception to production, focusing on reliability and user experience for both annotators and researchers. You will design and implement web interfaces, backend services, and data pipelines, working closely with researchers to understand and fulfill their data needs.

Anthropic

Anthropic is building reliable, interpretable, and steerable AI systems to be safe and beneficial for users and society. As the Data Operations Manager, you will be instrumental in building and scaling data operations for research teams focused on frontier AI capabilities. This role involves partnering with researchers to define and execute data strategies, managing vendor relationships, and overseeing the entire data pipeline from inception to production. While a strong understanding of what constitutes high-quality training data is important, the primary focus will be on strategic planning and execution to ensure the data operations directly contribute to model performance in critical areas like tool use accuracy, prompt injection robustness, and safety alignment.

Anthropic

As a Technical Program Manager on the reinforcement learning team, you will own the systems and programs that determine how fast our research moves. This involves providing a trustworthy read on the state of RL research and managing the review and prioritization processes that translate that understanding into critical decisions for production RL runs. You will need strong technical depth, including the ability to debug data pipelines, analyze RL transcripts for issues, and make real-time allocation and quality decisions when research or production runs encounter problems. Equally important is organizational effectiveness: navigating a fast-growing organization, identifying key individuals and teams across research, infrastructure, product, and data operations, and coordinating their efforts to maintain velocity. Join us in our mission to build AI systems that are safe, reliable, and beneficial to humanity.

Anthropic

We are seeking a Research Engineer for our Code RL team, focused on advancing AI models' capabilities in writing, editing, testing, debugging, and shipping real software. This role involves designing RL environments, coding tasks, and reward signals, as well as running training experiments on frontier models. You will diagnose model performance, improve pipeline speed and reliability, and contribute to areas like agentic coding behaviors, code correctness, and autonomous engineering. The position blends cutting-edge research with practical engineering to build high-quality, scalable AI systems.

Anthropic

Anthropic is seeking an exceptional Research Scientist to join its Life Sciences team. This role focuses on making Claude a superhuman life sciences research assistant, operating at the intersection of machine learning, software engineering, and biology. You will directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member, you will translate deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows, helping establish Anthropic as a leader in AI-accelerated biology and shaping how frontier models reason about computational biology tasks. This is a unique opportunity to shape how frontier AI models learn biology, working alongside top AI researchers on problems crucial for human health and scientific understanding.

Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. As an ML Systems Engineer on the Reinforcement Learning Engineering team, you will build and improve the critical algorithms and infrastructure that researchers use to train AI models like Claude. Your work will directly enable breakthroughs in AI capabilities and safety, focusing on enhancing the performance, robustness, and usability of these systems to accelerate research progress. You will support and empower the research team in their mission to build beneficial AI systems, specifically by building, maintaining, and improving the algorithms and systems used for finetuning production and research models with methods like RLHF.

Anthropic

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. For this role, interviews are conducted in Python, and the position may require responding to incidents on short notice, including weekends.

LangChain is seeking an experienced Research Engineer to join the LangSmith Engine team. This role focuses on enhancing the capabilities and efficiency of a proactive agent engineer that analyzes production traces, identifies failures, and implements fixes to prevent recurrence. You will study agent failures, build benchmarks, run experiments to improve performance, and translate successful ideas into production. This involves optimizing prompting, agent harnesses, model selection, fine-tuning, and post-training custom models, with a strong emphasis on measurable improvements to the overall agent. The role also requires an understanding of production engineering and system-level trade-offs, including cost, latency, reliability, and scalability, working closely with production engineers to ensure reliable real-world performance.

Fiddler is building trust into AI, especially with the rise of Generative AI and Agents. Our platform helps organizations deploy trustworthy and transparent AI solutions by monitoring, evaluating, securing, analyzing, and improving AI applications. We partner with AI-first organizations to establish responsible AI practices, enabling engineering teams and business stakeholders to understand AI outcomes. Joining Fiddler means making an impact by ensuring AI applications at production scale have operational transparency and security. This is an opportunity to be a trailblazer in the rapidly innovating AI and ML industry, contributing to AI Observability.

$220k - $260k

OpenAI

We are seeking exceptional researchers to push the frontier of safety mitigations for increasingly capable AI models. You will help derisk frontier models by developing novel safety mitigations and applying new techniques from domains like interpretability, control, and alignment. This role is critical in defining the future of safe AI systems at OpenAI and significantly impacting our mission to build and deploy safe AGI. The position requires strong technical depth and close cross-functional collaboration to ensure safety mitigations are enforceable, scalable, and effective, partnering with experts across misalignment, cybersecurity, and biology to develop a comprehensive safety stack.

Inflection AI

Inflection AI is seeking a hands-on technical leader to own the model-improvement loop, from data and training through evaluations, post-training, release criteria, and production feedback. This role sits at the intersection of research, production engineering, and model release, with the goal of shipping measurably better models for users. The ideal candidate will have prior experience leading significant model training or post-training initiatives and can make informed tradeoffs across data, compute, architecture, and quality to achieve a clear technical roadmap.

$400k - $550k

Luma is seeking a Research Scientist / Engineer to build the systems that enable reinforcement learning (RL) at frontier scale. This role involves coupling policy optimization with large fleets of inference workers, agentic environments, and reward/verification systems to transform model behavior into learning signals. RL is crucial for Luma's models to evolve from capable to useful. Operating RL at scale is a complex systems challenge, encompassing training, rollout generation, environment execution, and reward computation across thousands of GPUs, demanding speed, stability, and correctness. This position is ideal for someone with hands-on experience in post-training LLMs with RL, building environments and verifiers, and debugging large-scale asynchronous rollout pipelines.

$30k - $60k

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.

OpenAI

We are seeking a Research Engineer / Scientist to join our applied research team focused on developing new methods, models, and evaluation frameworks for the future of computing. This role will concentrate on building the learning and evaluation foundations that enable AI models to become more context-aware, adaptive, and useful over time. You will tackle challenges such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that require high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded, aiming for improved model behavior in real-world use rather than just benchmark performance. The ideal candidate is passionate about advancing AI systems beyond simple assistant interactions towards those that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value.

Crusoe is seeking a Senior Director, Developer Advocacy to be the public face of Crusoe Cloud for developers, ML engineers, and technical builders. This role requires someone equally comfortable presenting publicly and working technically, with the ability to build trust with practitioners and translate that into awareness and adoption. You will define how Crusoe Cloud engages with developers across social platforms and technical communities, creating a cohesive narrative that cuts through the noise. Your responsibilities will include engaging directly with developers at events, capturing their perspectives, and generating excitement for Crusoe Cloud through compelling content, especially short-form video. This position sits at the intersection of advocacy, content, and community, partnering with Developer Relations, Product, Engineering, and Marketing to make Crusoe Cloud a platform of curiosity and trust for technical audiences and decision-makers.

$280k - $300k

Harvey

Harvey is transforming legal and professional services by combining agentic AI, an enterprise-grade platform, and deep domain expertise. We are seeking a Research Engineer focused on post-training to scale the process of turning expert feedback and agent traces into significantly improved models. This role involves defining and running model training experiments, interpreting results, and collaborating with internal and external partners to enhance data, environments, graders, and training methodologies. The ideal candidate is a self-manager with extensive hands-on experience training open-weight models and the engineering depth to execute and debug experiments efficiently.

$231k - $340k