ML Engineer (Coding Agent Experience)

aitrainer; Deutschland; Vor Ort; EUR 391.567 - 557.687; Teilzeit

Zusammenfassung

aitrainer is looking for machine learning engineers to work on an exciting project evaluating frontier AI coding models through structured assessments. This role involves using AI coding agents to tackle complex tasks and applying professional judgment in ML workflows.

The position offers a flexible time commitment with compensation of $400 per accepted task, and tasks typically take 1-3 hours to complete. Suitable candidates will have at least 2 years of experience in machine learning and familiarity with AI coding tools.

Qualifikationen

• 2+ years of professional machine learning engineering experience.
• Experience building production ML systems or AI-powered products.
• Regular use of AI coding agents for ML tasks.

Aufgaben

• Use AI coding agents to complete complex ML engineering tasks.
• Evaluate model outputs and identify bugs or performance issues.
• Compare strengths and weaknesses of frontier AI models.

Kenntnisse

Machine learning engineering

AI coding tools

Model evaluation

Production ML systems

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Jobbeschreibung

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 1–3 hours after ramp-up.

• No fixed task limits.

• 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.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.