Research Engineer / Research Scientist, Tokens
About the Role
As a Research Engineer at Anthropic, you'll work on building large-scale ML systems from the ground up, focusing on making them safe, steerable, and trustworthy. You'll contribute to various aspects of our code and infrastructure, including improving cluster reliability, optimizing throughput, designing and running scientific experiments, and enhancing dev tooling. This is an "evergreen" role, meaning we continuously evaluate applications for top talent to join our team.
Responsibilities
- Optimize the throughput of new attention mechanisms
- Compare the compute efficiency of different Transformer variants
- Create datasets in formats easily consumable by models (e.g., a Wikipedia dataset)
- Scale distributed training jobs to thousands of GPUs
- Write design documents for fault tolerance strategies
- Develop interactive visualizations of attention mechanisms in language models
Requirements
- Significant software engineering experience
- Results-oriented mindset with a bias towards flexibility and impact
- Willingness to take on tasks outside your job description
- Enthusiasm for pair programming
- Interest in learning more about machine learning research
- Concern for the societal impacts of your work
Qualifications
- Minimum education: Bachelor’s degree or equivalent in a relevant field
- Experience with high-performance, large-scale ML systems
- Familiarity with GPUs, Kubernetes, PyTorch, or OS internals
- Experience with language modeling using transformers
- Knowledge of reinforcement learning
- Experience with large-scale ETL processes
Pay
Annual Salary: $350,000—$500,000 USD
Logistics
Location-based hybrid policy: 25% in-office requirement (some roles may require more). Visa sponsorship available, though not guaranteed for every role or candidate. We encourage applications from all qualified individuals, including those from underrepresented groups.
How We're Different
At Anthropic, we approach AI research as a collaborative, large-scale empirical science, focusing on high-impact work to advance steerable, trustworthy AI. Our team values communication, impact, and diverse perspectives. We’re headquartered in San Francisco and offer competitive benefits, including equity donation matching, generous leave policies, and flexible working hours.