ML Engineer - AI Coding Expert

Mercor; Toronto; On-site; CAD 179,000 - 289,000; Full time

Job summary

Mercor collaborates with a leading AI research lab on frontier code agents to assess and improve frontier AI coding models through structured evaluations. Contributors help advance realistic ML engineering workflows and model evaluation, focusing on production-ready deployment and robust inference systems.

The role emphasizes hands-on review of model-generated implementations, bug-hunting, and comparing outputs across frontier models, requiring strong engineering judgment for real-world ML

Qualifications

• 2+ years of professional machine learning engineering experience.
• Experience building production ML systems, deployment infra, 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 ML implementations and technical tradeoffs.
• Experience deploying ML systems to production is preferred.

Responsibilities

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

Skills

ML engineering

Production ML systems

LLM applications

AI coding agents

Model deployment infrastructure

Evaluation of model outputs

Problem solving

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Job description

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.