ML Engineer (Coding Agent Experience) | $85/hr Remote
Overview
We're looking for an ML Engineer to support a frontier code agents project in partnership with a leading AI research lab. You'll use advanced AI coding tools to evaluate and improve cutting-edge coding models, working through realistic machine learning workflows. This is a remote, sprint-based contract role with competitive hourly compensation — and spots are filling fast.
What You'll Do5
- 1Leverage frontier AI coding agents to complete complex ML and AI engineering tasks and assess model outputs.
- 2Review model-generated implementations covering model training, inference systems, MLOps, and LLM applications.
- 3Pinpoint bugs, edge cases, and performance bottlenecks in generated code and model behavior.
- 4Compare outputs from multiple frontier models, documenting their relative strengths and weaknesses.
- 5Apply professional engineering judgment to realistic production scenarios to determine whether model solutions are viable.
Requirements5
- 1At least 2 years of professional experience in machine learning engineering.
- 2Hands-on experience building production ML systems, deployment infrastructure, LLM applications, or AI-powered products.
- 3Regularly use AI coding agents like Cursor, Claude Code, Codex, Windsurf, or Gemini CLI.
- 4Ability to critically evaluate model-generated ML implementations and understand technical tradeoffs.
- 5Experience deploying ML systems to production is a plus.
Who Should Apply
The ideal candidate is a hands-on ML engineer who spends as much time in an AI coding agent as in a Jupyter notebook. You're comfortable evaluating model-generated code, have a sharp eye for failure modes, and can make sound judgment calls on realistic ML engineering problems. You're looking for a flexible, sprint-based contract that fits around your schedule and want to help shape the next generation of frontier coding models.
Salary Insight
$85/hour, paid per accepted task — typically $400 per task that takes 2–3 hours after initial ramp-up. Compensation is tied to accepted work.
Location
Required Skills
Application Tip
In your application, give concrete examples of how you've used AI coding agents on real ML projects — including any bugs you caught in generated code and how you evaluated model output for correctness.
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