Research Engineer, Discovery

Details

Anthropic is building reliable, interpretable, and steerable AI systems. The team’s goal is to build an AI scientist capable of solving long-term reasoning challenges and advancing the scientific frontier.

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

Responsibilities

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

Requirements

• 6+ years of highly relevant infrastructure engineering experience, 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 such as Docker and Kubernetes, including 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 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.
• A bachelor's degree or equivalent combination of education, training, and experience in a field relevant to the role.

Strong candidates may also have experience with:

• Language model training infrastructure and distributed machine learning frameworks such as PyTorch and JAX.
• Infrastructure for AI research labs or large-scale machine learning organizations.
• GPU/TPU architectures and language model inference optimization.
• Enterprise-scale cloud platforms such as AWS and GCP.
• VM and container orchestration.
• Workflow orchestration tools and experiment management systems.
• Large-scale reinforcement learning.
• Large-scale data pipelines using Beam, Spark, Dask, or similar technologies.

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. Staff are currently expected to work from one of Anthropic's offices at least 25% of the time, although some roles may require more office time. Anthropic sponsors visas and states that it will make reasonable efforts to obtain a visa for candidates who receive an offer, with assistance from an immigration lawyer.