Research Engineer, Environment Scaling

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

The Environment Scaling team builds the training environments that fuel reinforcement learning (RL) at scale to improve the intelligence of public models for novel verticals and use cases. This role combines ML research, data operations, and project management to create end-to-end RL environments: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance.

Responsibilities

• Improve and execute fine-tuning strategies for adapting Claude to new domains and tasks
• 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 environments for high-value tasks
• Develop and improve QA frameworks to catch reward hacking and ensure environment quality
• Partner with other RL research teams and product teams to translate capability goals into training environments and evaluations

Requirements

• Experience with fine-tuning large language models for specific domains or real-world use cases and/or domain expertise in an area where the team wants to make models more useful
• Experience with reinforcement learning, reward design, or training data curation for LLMs
• Comfortable managing technical vendor relationships and iterating quickly on feedback
• Ability to read through datasets to understand them and spot issues
• Strong project management and interpersonal skills
• Passion for making AI more useful and accessible across industries
• Comfortable with a role that mixes ML research, data operations, and project management

Strong candidates may also have

• Experience training production ML systems
• Familiarity with distributed systems and cloud infrastructure
• Domain expertise in target application areas
• Experience working with external vendors or technical partners

Compensation

Annual Salary: $350,000 - $850,000 USD

Logistics & Other Information

• Education requirements: At least a Bachelor's degree in a related field or equivalent experience
• Location-based hybrid policy: Currently, staff are expected to be in one of our offices at least 25% of the time (some roles may require more time in offices)
• Visa sponsorship: The company states they do sponsor visas and retain an immigration lawyer to assist, though sponsorship is not guaranteed for every role/candidate

Benefits

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration. They provide guidance for candidates on acceptable AI usage during the application process.