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AnthropicAnthropicSan Francisco, CA

Research Engineer, Computer Use

Research Engineer advancing Claude's computer use capabilities through experiments, RL environments, evaluations, and infrastructure for perception and agentic tasks. Requires Python, ML training/evaluation experience, and a focus on safe AI.

500k – 850k/yr
Hybrid5+ YOEML Engineering

About the role

Key Responsibilities

  • Design and run experiments to improve Claude's perception and agentic capabilities
  • Develop robust, reliable evaluation frameworks for measuring our models' ability to complete complex computer tasks
  • Build and improve computer use and vision reinforcement learning training environments
  • Create pipelines and tools to test and validate complex RL environments
  • Collaborate with teams across the model training and infrastructure stack to improve our production training setup
  • Partner with product teams to bring research advances into production

Minimum Qualifications

  • Software engineering experience and proficiency in Python
  • Experience training, fine-tuning, or evaluating machine learning models
  • Strong communication skills and a collaborative working style
  • Care about the societal impacts and safety of your work

Preferred Qualifications

  • Experience training models for computer use or other agentic capabilities
  • Experience with reinforcement learning, particularly in long-horizon or sparse-reward settings
  • Familiarity with multimodal model training
  • Experience building evaluations or benchmarks for agentic systems
  • Experience building reinforcement learning environments, simulation systems, or large-scale ML infrastructure
  • Experience working closely with product teams to drive model improvements

Education

  • Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role

Skills

PythonMachine LearningReinforcement LearningMultimodal ModelsRl EnvironmentsModel TrainingModel EvaluationModel Fine-TuningAgentic SystemsBenchmarksML Infrastructure

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