Research Engineer, Discovery

Details

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. The Discovery team is focused on building an AI scientist capable of solving long-term reasoning challenges and advancing the scientific frontier.

As a Research Engineer, you will work end to end across the model stack, identifying and addressing infrastructure blockers on the path to scientific AGI. The role involves language model training, evaluation, inference, performance optimization, distributed systems, VM/sandboxing/container deployment, and large-scale data pipelines.

Responsibilities

• Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments.
• Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities.
• Develop robust and reliable evaluation frameworks for measuring progress toward scientific AGI.
• Build scalable and performant VM, sandboxing, and container architectures to safely execute long-horizon AI tasks and scientific workflows.
• Collaborate to translate experimental requirements into production-ready infrastructure.
• Develop large-scale data pipelines to handle advanced language model training requirements.
• Optimize large-scale training and inference pipelines for stable and efficient reinforcement learning.

Requirements

• 6+ years of highly relevant experience in infrastructure engineering, with demonstrated expertise in large-scale distributed systems.
• Strong communication and collaboration skills.
• Deep knowledge of performance optimization techniques and system architectures for high-throughput machine learning workloads.
• Experience with containerization technologies, including Docker and Kubernetes, and orchestration at scale.
• A proven track record of building large-scale data pipelines and distributed storage systems.
• Ability to diagnose and resolve complex infrastructure challenges in production environments.
• Ability to work effectively across the full machine learning stack, from data pipelines to performance optimization.
• Experience collaborating with researchers to scale experimental ideas.
• Ability to rapidly iterate from experimentation to production in fast-paced environments.
• Bachelor's degree or an equivalent combination of education, training, and/or experience in a field relevant to the role, as demonstrated through coursework, training, or professional experience.

Additional Qualifications

• Experience with language model training infrastructure and distributed machine learning frameworks such as PyTorch and JAX.
• Background building infrastructure for AI research labs or large-scale machine learning organizations.
• Knowledge of GPU/TPU architectures and language model inference optimization.
• Experience with cloud platforms such as AWS and GCP at enterprise scale.
• Familiarity with VM and container orchestration.
• Experience with workflow orchestration tools and experiment management systems.
• Experience with large-scale reinforcement learning.
• Comfort with large-scale data pipelines using tools such as Beam, Spark, or Dask.

Benefits

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and an office space for collaboration. Anthropic expects staff to work from one of its offices at least 25% of the time, although some roles may require more office time. Anthropic sponsors visas when possible and retains an immigration lawyer to provide assistance.

The annual salary range is $350,000–$850,000 USD.