AI/ML Engineer - Fully Remote | Upto $85/hr

mercor; United States; Remote; USD 117,000 - 138,000; Full time

Job summary

Mercor is seeking an ML Engineer (Coding Agent Experience) for a contract role with remote work. You will leverage frontier AI coding agents to tackle advanced ML engineering tasks and contribute to evaluation of model-generated implementations.

Ideal candidates have hands-on experience deploying production ML systems and comfort with ML tooling, inference pipelines, and MLOps. This contract offers compensation per accepted task with remote collaboration.

Qualifications

• 2+ years of professional machine learning engineering experience.
• Experience building production ML systems and deployment infrastructure.
• Regular use of AI coding agents (Cursor, Claude Code, Codex, Windsurf, Gemini CLI, etc.).
• Ability to evaluate model-generated ML implementations and tradeoffs.

Responsibilities

• Use frontier AI coding agents to complete and evaluate ML tasks.
• Review model-generated implementations involving training, inference, and MLOps.
• Identify bugs, edge cases, performance issues, and failure modes.
• Compare outputs from frontier models and assess strengths and weaknesses.
• Apply professional engineering judgment to realistic ML scenarios.

Skills

Machine Learning Engineering

Production ML systems

LLM applications

AI coding agents usage

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: ML Engineer (Coding Agent Experience)
Type: Contract
Compensation: $85/hour
Location: Remote

Responsibilities

• 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 in AI models.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic ML engineering scenarios.

Qualifications

Must-Have

• 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.

Preferred

• Experience deploying ML systems to production.

Compensation & Legal

• $400 per accepted task
• Compensation is tied to accepted work.