Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Data Pipelines
LLM
Reinforcement Learning @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About the role
The Domain Scaling team has the goal to make Claude world-class at real-world knowledge work in domains like finance, healthcare, and legal. This is a unique role that combines executing directly on applied research and data sourcing (real-world and synthetic) to improve our models. You’ll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.
Responsibilities
- Own the data strategy for knowledge work verticals end-to-end, from task sourcing through RL training
- Manage technical relationships with external data vendors, including evaluation of data quality and reward design
- Collaborate with domain experts to design data pipelines and evaluations
- Explore novel ways of creating RL envs for high value tasks
- Develop and improve QA frameworks to catch reward hacking and ensure env quality
- Run generalization experiments to measure how data strategy changes improve model capabilities
- Partner with other RL research teams and product teams to translate capability goals into training envs and evals
Requirements
- Have experience with fine-tuning large language models for specific domains or real-world use cases
- Have experience with reinforcement learning, reward design, or training data curation for LLMs
- Are comfortable managing technical vendor relationships and iterating quickly on feedback
- Find value in reading through datasets to understand them and spot issues
- Have strong cross-functional collaboration skills
- Are passionate about making AI more useful and accessible across different industries
- Are excited about a role that includes a combination of applied research and hands-on data work
Logistics
- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
- Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
More jobs at Anthropic
Recruiter, Applied AI
Anthropic · San Francisco, United States
USD 175,000-240,000 per year
Staff Software Engineer, GTM Systems
Anthropic · San Francisco, United States
USD 320,000-405,000 per year
Evals Infrastructure Tech Lead / Manager
Anthropic · San Francisco, United States
USD 500,000-850,000 per year
Manager, IT Support
Anthropic · San Francisco, United States, New York City, United States, Seattle, United States
USD 230,000-265,000 per year
Technical Program Manager, GTM Systems
Anthropic · San Francisco, United States, New York City, United States
USD 290,000-365,000 per year
Similar jobs
Research Engineer, Life Sciences
Anthropic · San Francisco, United States
USD 350,000-500,000 per year
Machine Learning Engineer, LLM Evals & Observability
Glean · United States
USD 200,000-300,000 per year
Machine Learning Engineer, LLM Evals & Observability
Glean · San Francisco, United States
USD 200,000-300,000 per year
Staff+ Software Engineer, GRC Platform
Anthropic · San Francisco, United States, New York City, United States, Seattle, United States
USD 320,000-405,000 per year
Staff+ Security Engineer, Risk Engineering
Anthropic · San Francisco, United States, New York City, United States, Seattle, United States
USD 320,000-405,000 per year
Research Engineer, Chip Design RL (Reinforcement Learning)
Anthropic · San Francisco, United States, New York City, United States
USD 500,000-850,000 per year
Finance Systems Integration Engineer
Anthropic · San Francisco, United States, Seattle, United States
USD 205,000-270,000 per year
Staff Software Engineer, Data Engineering Solutions
Stripe · South San Francisco, United States, Seattle, United States, Toronto, Canada
USD 224,000-336,000 per year