ML Engineer (Coding Agent Experience)

About this role

**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.

Skills & domains

• ai-training
• rlhf
• sme
• annotation
• Data Analysis