Research Engineer, Computer Use
Core
Advancing AI models' ability to reliably and safely operate real software by designing experiments, building evaluation frameworks, and creating reinforcement learning training environments.
Role type
Research Engineer (Computer Use / Agentic AI)
Builds
Computer use and vision reinforcement learning training environments, evaluation frameworks, and pipelines for testing complex RL environments.
Domain
Artificial Intelligence / Machine Learning / Computer Use
Deliverable
production ML models
Required skills
Python, machine learning model training and fine-tuning, experiment design, evaluation framework development, reinforcement learning, collaboration with product teams
Preferred skills
training models for agentic capabilities, reinforcement learning in long-horizon or sparse-reward settings, multimodal model training, building benchmarks for agentic systems, building large-scale ML infrastructure
Technologies
Python, reinforcement learning environments, multimodal models
Responsibilities
Design and run experiments to improve model perception and agentic capabilities; Develop robust evaluation frameworks for measuring model 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 model training and infrastructure teams to improve production training setup; Partner with product teams to bring research advances into production
Seniority
Mid-to-Senior, hands-on IC
