Research Engineer/Research Scientist, Pre-Training

Details

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. They are seeking a Research Engineer to join the Pre-training 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.

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 their understanding of large language models
• Optimize and scale their 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

Preferred Experience

• 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

Sample Projects

• Optimizing the throughput of novel attention mechanisms
• Comparing compute efficiency of different Transformer variants
• Preparing large-scale datasets for efficient model consumption
• Scaling distributed training jobs to thousands of GPUs
• Designing fault tolerance strategies for their training infrastructure
• Creating interactive visualizations of model internals, such as attention patterns

Logistics

• Location-based hybrid policy: They expect all staff to be in one of their offices at least 25% of the time (some roles may require more time).
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Visa sponsorship: They do sponsor visas, but not for every role and candidate. If they make an offer, they will make every reasonable effort to get you a visa and retain an immigration lawyer to help.

How they’re different

They believe the highest-impact AI research will be big science, and work as a single cohesive team on a few large-scale research efforts. They host frequent research discussions and value communication skills.

Come work with us!

They offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a collaborative office space.