ML Engineer (Coding Agent Experience)

About the Role

\- Mercor is partnering with a leading AI research lab to support a Frontier Code Agents project.

\- Contributors help evaluate and improve frontier AI coding models through structured technical assessments.

\- The work focuses on realistic machine learning engineering workflows and model evaluation.

\- Spots are limited and filling quickly on a first come, first serve basis.

What You'll Do

\- Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.

\- Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.

\- Identify bugs, edge cases, performance issues, and failure modes.

\- Compare outputs from multiple frontier models and assess their strengths and weaknesses.

\- Apply professional engineering judgment to realistic ML engineering scenarios.

Time Commitment

\- Sprint based project that runs in 12-24 hour stretches based on client requirement.

Compensation

\- $400 per accepted task.

\- Typical tasks take approximately 2–3 hours after ramp-up.

\- Compensation is tied to accepted work.

Who Should Apply

\- 2+ years of professional machine learning engineering experience.

\- Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.

\- Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.

\- Ability to evaluate model-generated machine learning implementations and technical tradeoffs.

\- Experience deploying ML systems to production is preferred.