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Research Engineer, Visual Knowledge Work

Anthropic · New York City

Senior 🇬🇧 English
Computer Vision Software Engineering Reinforcement Learning Reward Design Training Data Curation Large-scale pretraining

Job description

About the role

Anthropic is seeking a Research Engineer to advance visual and spatial reasoning capabilities within large language models. The role sits on the Vision team and blends applied research with hands‑on data creation, evaluation, and reinforcement‑learning environment design.

Key responsibilities

  • Own the end‑to‑end data strategy for vision capabilities, including building evaluations and scaling RL environments.
  • Write task specifications for external vendors, assess visual data and annotation quality, and iterate on reward designs.
  • Develop QA frameworks that detect reward hacking and maintain environment quality at scale.
  • Run generalisation experiments to measure the impact of data‑strategy changes on multimodal performance.
  • Collaborate with pretraining, RL, and product teams to align research outcomes with real‑world knowledge‑work needs.

Required profile

  • 7+ years of experience in machine learning, computer vision, and software engineering.
  • Hands‑on experience with reinforcement learning, reward design, or training‑data curation for large language or vision‑language models.
  • Familiarity with the architecture, training, and operation of large vision‑language models.
  • Comfort managing technical vendor relationships and iterating quickly on feedback.
  • Results‑oriented mindset with a focus on impact and societal implications of AI work.

Required skills

  • Machine Learning (ML)
  • Computer Vision
  • Software Engineering
  • Reinforcement Learning
  • Reward Design
  • Training Data Curation
  • Large Vision‑Language Models
  • Evaluation and benchmark design
  • Large‑scale pretraining, supervised learning, and RL
  • Deep learning for images, video, and other modalities
  • Complex agentic system development using LLMs
  • Large‑scale ETL and data‑pipeline development

Questions fréquentes

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Source : ats:greenhouse

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Published 4 weeks ago

Expires 1 month from now

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Anthropic

New York City