Research Engineer (Pretraining Scaling)

• Anthropic’s ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company’s future and our mission to build safe, beneficial AI systems
• As a Research Engineer on this team, you’ll ensure our frontier models train reliably, efficiently, and at scale
• This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems
• This role lives at the boundary between research and engineering
• You’ll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination
• During launches, the team works in tight lockstep, responding to production issues that can’t wait for tomorrow
• Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability
• Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
• Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
• Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
• Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
• Add new capabilities to the training codebase, such as long context support or novel architectures
• Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
• Contribute to the team’s institutional knowledge by documenting systems, debugging approaches, and lessons learned
• This is not a typical research engineering role
• The work is highly operational—you’ll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty
• During launches, the team often works extended hours and may need to respond to issues on evenings and weekends
• However, this operational intensity comes with extraordinary learning opportunities
• You’ll gain hands-on experience with some of the largest, most sophisticated training runs in the industry
• You’ll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can’t be easily transferred
• For people who thrive on this type of work, it’s uniquely rewarding. We’re building a close-knit team of people who genuinely care about doing excellent work together

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents
• Inclusive fertility benefits via Carrot Fertility
• 22 weeks of paid parental leave
• Flexible paid time off and absence policies
• Mental health support for you and your dependents
• Competitive salary and equity packages
• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
• Retirement plans with competitive matching
• Life and income protection plans
• $500/month flexible wellness and time saver stipend
• Commuter benefits
• Annual education stipend
• Home office stipends
• Relocation support for those moving for Anthropic
• Daily meals and snacks in the office- Experience with production ML systems, observability tools, or evaluation infrastructure
• Care about the societal impacts of AI and responsible scaling
• Genuinely enjoy both research and engineering work—you’d describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
• Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
• Contributed to open-source LLM frameworks (e.g., open_lm, llm-foundry, mesh-transformer-jax)
• Published research on model training, scaling laws, or ML systems
• Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence
• Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
• Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
• Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
• Excel at debugging complex, ambiguous problems across multiple layers of the stack
• Are passionate about the work itself and want to refine your craft as a research engineer
• We require at least a Bachelor’s degree in a related field or equivalent experience
• Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
• We encourage you to apply even if you do not believe you meet every single qualification- Applications will be reviewed on a rolling basis