over 1 year ago
Base Salary
$315k - $510k/yr
Responsibilities
- Implement and optimize post-training techniques at scale on frontier models
- Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
- Develop tools to measure and improve model performance across multiple dimensions
- Translate emerging research techniques into production-ready implementations with research teams
- Debug complex training-pipeline and model-behavior issues
- Establish best practices for reliable and reproducible model post-training
Requirements
- Bachelor’s degree in a related field or equivalent experience
- Strong software engineering skills and experience building complex ML systems
- Experience training, fine-tuning, or evaluating large language models
- Required proficiency in Python, deep learning frameworks, and distributed computing
- Comfort with large-scale distributed systems and high-performance computing
- Ability to analyze and debug model training processes
- Experience with LLMs is a significant plus
- Interest in AI safety and responsible deployment
- Strong collaboration and communication skills
Benefits
- Hybrid work with staff expected in an office at least 25% of the time
- Visa sponsorship with immigration-lawyer support
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Collaborative office space
Tech Stack
Categories
AI ResearchML Engineering
About Anthropic
Anthropic builds large language models and the Claude AI assistant for developers and enterprises, offered via API access and enterprise plans. Founded in 2021 and headquartered in San Francisco, it distributes Claude through its own platform and via partners such as Amazon Bedrock and Google Cloud’s Vertex AI. Its work emphasizes model reliability, interpretability, and practical tooling for tasks like coding assistance, analysis, and customer support automation.