Research Engineer, Computer Use
This is an analysis of the public job description. It is not a confirmed description of this company's interview process, and no company has reviewed or endorsed it.
What the posting clearly emphasises
- Agentic computer use and perception.
- Long-horizon reinforcement learning and RL environments.
- Evaluations and benchmarks, production training, product collaboration.
What that likely means for preparation
- Expect environment and harness design questions: screen state, action spaces, recovery from a wrong click, and how you score partial progress.
- Long-horizon credit assignment and failure taxonomies are more relevant than single-step accuracy.
- Be ready to talk about a training run you actually shipped into a product, not only an experiment.
What stays unknown about the loop
- Whether an agent-building exercise is part of the loop, and how much perception depth is expected.
- The round order, count and length. Postings describe the job, not the loop.
- Whether AI assistants are allowed, required or banned in any coding exercise.
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