RLHF Jobs

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

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.

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 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 is seeking a Research Operations Specialist to manage the production of risk reports, which are long-form technical documents detailing potential risks from AI models. This role involves coordinating contributions from numerous researchers, managing timelines, and ensuring the final document is cohesive and accurate. You will also perform substantive editorial work, transforming technical findings and threat models into clear prose, and ensuring consistency across various safety artifacts like system cards and Responsible Scaling Policy updates. This position requires a blend of project management and communication skills to make complex AI safety assessments accessible to a broad audience while maintaining precision.

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.

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

Together AI

The Turbo Research team focuses on making post-training and reinforcement learning for large language models efficient, scalable, and reliable. This work intersects RL algorithms, inference systems, and large-scale experimentation, where inference costs significantly impact training efficiency and the practicality of learning algorithms. As a research intern, you will investigate RL and post-training methods whose performance and scalability are closely tied to inference behavior, co-designing algorithms and systems. Projects aim to enable new experimental regimes, including larger models, longer rollouts, and more complex evaluations, by re-evaluating the interaction between inference, scheduling, and training.

AI research at WRITER focuses on building the scientific foundation for ambitious enterprise AI deployments. As a staff AI research scientist, you will drive a high-impact research agenda centered on large language models, agentic reasoning, and system-level capabilities essential for enterprise-scale AI. This role offers a unique opportunity to advance the field while directly contributing to products used by hundreds of thousands daily. You will work on post-training, planning, multi-step reasoning, and agentic workflows, directly shaping the future of enterprise AI performance and scalability. The role provides resources, infrastructure, and cross-functional support to pursue and implement ambitious ideas rapidly.

Together AI

The Turbo team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems. We are responsible for building and managing the systems that power Together's API, focusing on high-performance inference and RL/post-training engines capable of operating at production scale. Our core mission is to advance the frontiers of efficient inference and RL-driven training, aiming to make models significantly faster and more cost-effective to run, while simultaneously enhancing their capabilities through RL-based post-training methods. This role involves working across the entire stack, from RL algorithms and training engines to kernels and serving systems, to develop and refine state-of-the-art models using RL pipelines. We value individuals with deep expertise in one area and a strong willingness to collaborate and grow across others.

$200k - $280k

Together AI

As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to strategic customers, assisting production AI teams with leveraging high-quality models and performing inference at scale. You will act as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment, partnering with Solutions Architects. FDEs add significant value by ensuring complex Proofs of Concept (POCs) are met, facilitating platform adoption, and guiding tailored optimization efforts, directly impacting customer success and company growth.

$270k - $300k

Together AI

This research engineering role focuses on translating new Reinforcement Learning (RL) algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together's API. The Core ML team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems, building and maintaining high-performance inference and RL engines at production scale. The goal is to significantly improve model speed, cost-efficiency, and capabilities through RL-based post-training. This position requires a blend of algorithmic understanding and systems engineering, with opportunities to work across the entire stack from RL algorithms and training engines to kernels and serving systems, ultimately driving measurable improvements in latency, throughput, cost, and model quality at scale.

$200k - $280k

Scale AI

Scale is at the forefront of the AI revolution, developing data engines and technologies that power the world's leading LLMs. This role focuses on leading critical programs within the Platform and Security Engineering teams, overseeing the design and development of core data storage systems and security initiatives. You will drive company-wide programs, improve processes, and ensure alignment with industry standards, gaining exposure to the cutting edge of AI adoption across various sectors. The work is crucial for making AI models safe, aligned, and useful through human evaluation and reinforcement learning.

$181k - $226k

Scale AI

Scale is at the forefront of the AI revolution, building the Generative AI Data Engine and other products that power the world's most advanced LLMs. The Platform Engineering team is foundational to these efforts, responsible for designing and developing shared platforms, architecting core cloud infrastructure, and redefining software development processes. This role offers exposure to the cutting edge of AI development across various sectors, from startups to governments. You will drive the design and implementation of critical platforms, collaborate with cross-functional teams, and proactively improve engineering practices. This is an opportunity to shape the future of AI infrastructure and contribute to some of the most important work in how humanity interacts with AI.

$216k - $270k

Scale AI

As a Technical Program Manager, you will partner with our Frontier Agent Engineering teams on enterprise customer engagements, owning operational execution and delivery of technical work by managing timelines, milestones, risks, and dependencies. You will drive the strategic alignment and end-to-end execution of critical Enterprise initiatives, serving as the core communication backbone between engineering, product, and executive leadership. Operating in a demanding AI environment, you will translate technical complexity into clear execution strategies, proactively mitigate risks, and ensure engineering teams deliver reliable, high-value solutions at scale.

$211k - $264k

Scale AI

Scale Labs is seeking talented researchers to join a new team focused on policy research, bridging the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. This role will tackle fundamental challenges in building AI agents that are safe and aligned with humans, researching agent capabilities, designing evaluation harnesses, building exploits and mitigations for failure modes, and characterizing risks of multi-agent systems. The team collaborates broadly across industry, the public sector, and academia, regularly publishing findings.

$216k - $270k

Scale AI

Scale Labs is seeking a Research Scientist focused on AI Controls and Monitoring to join a new team dedicated to policy research. This role will bridge the gap between AI research and policymakers, focusing on scientific decisions about AI risks and capabilities. The team tackles challenges in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. You will design methods, systems, and experiments to ensure advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. This role involves collaboration across industry, the public sector, and academia, with regular publication of findings.

$216k - $270k

Scale AI

Scale Labs is seeking talented researchers to join a new team focused on policy research, bridging the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. This role will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer and better understood. You will design and run post-training pipelines, develop interpretability-informed evaluations, and collaborate with policymakers, engineers, and other researchers to translate findings into actionable safety standards and best practices.

$216k - $270k

Scale AI

Scale is seeking a Forward Deployed Product Manager (FDPM) to drive the success of enterprise AI deployments. This role is embedded with customers, focusing on achieving real production outcomes and translating operational realities into actionable product insights. Unlike a traditional roadmap PM or solutions engineer, the FDPM owns product outcomes within a portfolio of enterprise accounts, building trust with senior stakeholders, guiding deployments to production, and identifying product versus execution bottlenecks. The ideal candidate can differentiate between stated customer needs, underlying problems, and optimal platform solutions, having previously shipped products into large organizations.

$206k - $300k

Scale AI

Scale is at the forefront of the AI revolution, developing data engines and technologies that power the world's leading LLMs and generative models. This role is on the Platform Engineering team, responsible for the foundational data infrastructure that supports these cutting-edge AI products. You will lead the design and development of core data storage, streaming, caching, and indexing platforms, gaining exposure to the rapidly evolving AI landscape across various industries. The work involves driving architecture, implementation, and reliability of these critical systems, collaborating with stakeholders, and mentoring junior engineers.

$252k - $315k