Applied Researcher - Computer Use

The role

You will build post-training and evaluation systems for multimodal agents operating browsers, desktops, and cross-application workflows. The work involves turning real workflows and traces into environments, rewards, and experiments.

What you will do

• Turn workflows into tasks, environments, evaluations, and reward signals
• Run post-training experiments against real baselines and deploy what works
• Build long-horizon computer-use environments from real workflows
• Train agents to recover from interface changes, partial failures, and ambiguous intermediate states
• Develop evaluations that distinguish genuine completion from plausible-looking behavior
• Own multimodal environments built from partner workflows, demonstrations, tools, interface state, and outcome criteria
• Own browser, desktop, and cross-application agents with reliable sandbox and boundary enforcement
• Own training and evaluation from demonstrations, interventions, production failures, synthetic tasks, and verifiable outcomes
• Own experiments on recovery and generalization across applications, layouts, permissions, and deployment contexts
• Work directly with customers, users, or research partners

Required qualifications

• Relevant experience: multimodal agents, computer use, browser or desktop automation, RL, imitation learning, HCI, embodied agents, or long-horizon agent evaluation
• Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops
• Strong experimental judgment: meaningful baselines, careful trace inspection, clear failure attribution, and a willingness to change direction when the evidence changes
• Strong Python and the ability to build artifacts that other researchers and engineers can run, inspect, and extend
• Comfort owning ambiguous problems and keeping partners and teammates current as you resolve them

Nice to have

• Publications
• Open-source systems
• Benchmarks
• Shipped products

Benefits

• Cash Compensation Range of $150-300k + equity incentives
• Flexible Work (San Francisco, New York, London, or remote)
• Visa Sponsorship & relocation support
• Professional Development budget
• Team Off-sites & conference attendance

Before you apply

• Show something difficult you built, what failed, and how the evidence changed your approach

About the company

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.