What the role delivers

One computer vision engineer's capacity, working on your product.

Skills and scope are agreed before delivery starts, so the first sprint is productive rather than a ramp-up month. The work runs to the same backlog, the same repositories and the same definition of done as your own team's.

PythonPyTorchOpenCVYOLOONNX
  • Feature development

    LLM-powered features taken from prototype to production.

  • Retrieval and integrations

    Model providers, vector stores and your existing APIs connected.

  • Evaluation

    Evaluation sets, guardrails and prompt history kept documented.

  • Quality gates

    Tests, review and monitoring on everything that reaches users.

160 h
Typical monthly capacity for this role
Fixed
Monthly price, unaffected by leave or holidays
2–6 weeks
From signed scope to delivery starting
Monthly
Cycle to raise or lower committed hours
FAQ

Questions about this role.

Can I choose the seniority level?

Yes. Junior through principal AI engineers are available, priced by level. We'll recommend a level based on the scope you share before delivery starts.

What if the stack isn't listed above?

Tell us what you use. The list above is what we see most often, not a limit — we'll confirm fit for your exact setup at scoping.

Can I add a second AI engineer later?

Yes, at the next monthly cycle. Capacity moves with your roadmap rather than locking you into the original scope.

Who owns the code the AI engineer writes?

You do. Work happens in your repositories, under your license terms, from the first commit.

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