Research Engineer, Visual Knowledge Work

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We are looking for a research engineer to join the Vision team, owning the end-to-end process of creating training data and RL environments targeting visual knowledge work.

• Own the data strategy for vision capabilities end-to-end, from building evals and scaling RL environments.
• Manage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design.
• Develop and improve QA frameworks that catch reward hacking and ensure environment quality at scale.
• Run generalization experiments to measure how data strategy changes improve multimodal capabilities on held-out evaluations.
• Partner with pretraining, RL, and product teams.

• Have 7+ years of ML, computer vision, and software engineering experience.
• Have experience with reinforcement learning, reward design, or training data curation for large language or vision-language models.
• Are familiar with the architecture, training, and operation of large vision language models.
• Are comfortable managing technical vendor relationships and iterating quickly on feedback.
• Are results-oriented, with a bias towards flexibility and impact.
• Care about the societal impacts of your work.

• Experience designing evals or benchmarks for LLMs or vision language models.
• Large-scale pretraining, SL, and RL on language models.
• Deep learning research on images, video, or other modalities.
• Developing complex agentic systems using LLMs.
• Large-scale ETL and data pipeline development.

• Writing a vendor-facing specification for a new family of visual RL training tasks.
• Running experiments to determine ideal training datamixes and parameters for a synthetically generated vision dataset.
• Finetuning Claude to maximize its performance using a particular set of agent tools/skills.

Annual Salary: $350,000—$850,000 USD.

Location: New York City, NY; San Francisco, CA; Seattle, WA. Hybrid policy: all staff in one of our offices at least 25% of the time. Minimum education: Bachelor’s degree or equivalent. Required field: relevant to the role. Minimum years of experience: correlates with internal job level. Visa sponsorship: we do sponsor visas.