Anthropic
Research Engineer, Production Model Post-Training
$350K–$500K
San Francisco, CA +5 · Full-time · Posted Apr 1, 2025
- Location
- San Francisco, CA
New York City, NY
Seattle, WA
New York, New York, United States
San Francisco, California, United States
Seattle, Washington, United States - Experience
- Years required correlate with internal job level; candidates at various experience levels are welcome, with a preference for senior engineers with hands-on frontier AI experience.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, the company will make every reasonable effort to obtain a visa.
About the job
Train and improve production Claude models by researching, implementing, and scaling post-training techniques focused on model capabilities, alignment, and safety.
What you'll do
- Implement and optimize post-training techniques and recipes for frontier models.
- Build and run reliable pipelines for model fine-tuning and evaluation; develop tools to measure and improve performance.
- Translate research into production-ready implementations, debug training and model behavior, and establish reproducible practices.
What they ask for
- Proficiency in Python, deep learning frameworks, and distributed computing.
- Strong software engineering skills and experience building complex ML systems.
- Experience training, fine-tuning, or evaluating large language models.
- Ability to analyze and debug training processes and work with large-scale distributed systems and high-performance computing.
Nice to have
- Experience with LLMs.
- Interest in AI safety and responsible deployment.
Pay
$350,000 — $500,000 USD annual base salary
Tools
Python, deep learning frameworks
AI focus
Post-training frontier AI models, including Constitutional AI, RLHF, and other alignment methodologies, to improve capabilities, alignment, safety, and production quality.
Model-written summary · the original posting is authoritative