Anthropic · San Francisco/New York City/Seattle · Hybrid
Research Engineer, Reward Models
1/13/2025
Description
- Help implement novel reward modeling architectures and techniques
- Optimize training pipelines
- Build and optimize data pipelines
- Collaborate across teams to integrate reward modeling advances into production systems
- Communicate engineering progress through internal documentation and potential publications
Qualifications
- Have a strong engineering background in machine learning, with demonstrable expertise in preference learning, reinforcement learning, deep learning, or related areas
- Are proficient in Python, deep learning frameworks, and distributed computing
- Are familiar with modern LLM architectures and alignment techniques
- Have experience with improving model training pipelines and building data pipelines
- Are comfortable with the experimental nature of frontier AI research
- View research and engineering as complementary disciplines and are willing to implement some research ideas
- Can clearly communicate complex technical concepts and research findings
- Have a deep interest in AI alignment and safety
- Proficiency in Python and experience with deep learning frameworks is required for this role
Benefits
$315,000 - $340,000 USD