Machine Learning Engineer - Fully Remote | Upto $85/hr

mercor; Deutschland; Remote; EUR 98,000 - 117,000; Full time

Job summary

Mercor is seeking an ML Engineer (Coding Agent Experience) for remote, contract work. You will use frontier AI coding agents to tackle complex ML engineering tasks, including training, deployment, and MLOps.

Candidates should have 2+ years of ML engineering experience with production ML systems and experience with tools like Cursor, Claude Code, Codex, Windsurf, and Gemini CLI. Compensation is $85/hour with an additional $400 per accepted task.

Qualifications

• 2+ years of professional ML engineering experience.
• Experience building production ML systems and deployment infra.
• Regular use of AI coding agents (Cursor, Claude Code, Codex, Windsurf, Gemini CLI) or similar.

Responsibilities

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

Skills

ML engineering

Production ML

LLM applications

Model deployment

AI tooling

AI coding agents

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

Role 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.
• 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.