About the Role
Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pretraining team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. This role is crucial for advancing our understanding of large language models and optimizing our training infrastructure to improve efficiency and reliability.
Responsibilities
- Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development.
- Independently lead small research projects while collaborating with team members on larger initiatives.
- Design, run, and analyze scientific experiments to advance our understanding of large language models.
- Optimize and scale our training infrastructure to improve efficiency and reliability.
- Develop and improve dev tooling to enhance team productivity.
- Contribute to the entire stack, from low-level optimizations to high-level model design.
Requirements
- Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
- Strong software engineering skills with a proven track record of building complex systems
- Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
- Familiarity with large-scale machine learning, particularly in the context of language models
- Ability to balance research goals with practical engineering constraints
- Strong problem-solving skills and a results-oriented mindset
- Excellent communication skills and ability to work in a collaborative environment
- Care about the societal impacts of your work
- At least a Bachelor's degree in a related field or equivalent experience.
Qualifications
- Work on high-performance, large-scale ML systems
- Familiarity with GPUs, Kubernetes, and OS internals
- Experience with language modeling using transformer architectures
- Knowledge of reinforcement learning techniques
- Background in large-scale ETL processes
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Lovely office space
- Visa sponsorship