ML Platform Engineer | Remote

CodeGeniusRecruit; United States; On-site; USD 96,000 - 138,000; Part time

Job summary

CodeGeniusRecruit in the United States is seeking a skilled machine learning engineer to take on sprint-based tasks that run in 12-24 hour stretches. You will build and evaluate production ML components, using coding agents to drive model deployment, training, inference, and MLOps across real-world systems.

You will review model-generated code, identify bugs and performance issues, compare outputs from multiple models, and apply practical engineering judgment to tradeoffs.

Qualifications

• Strong experience in machine learning engineering.
• Experience building production ML systems and deployment infra.
• Experience with LLM applications and intelligent software.
• Familiar with coding agents and productivity tools.
• Ability to evaluate model-generated ML implementations and tradeoffs.

Responsibilities

• Complete and evaluate complex ML engineering tasks using coding agents.
• Review model-generated implementations involving training, inference, and MLOps.
• Identify bugs, edge cases, performance issues and failure modes.
• Compare outputs from multiple models and assess strengths and weaknesses.
• Apply engineering judgment to real-world ML scenarios.

Skills

ML engineering

Production ML

Model deployment

LLM apps

Coding agents

Developer tools

Job description

Commitment: Sprint-based project running in 12-24 hour stretches based on project requirements

Commission: $85/hour (Typical accepted tasks pay approximately $400 and take 2-3 hours after ramp-up).

What You'll Be Doing

Complete and evaluate complex machine learning engineering tasks using coding agents.

Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.

Identify bugs, edge cases, performance issues, and system failure modes.

Compare outputs from multiple models and assess strengths and weaknesses.

Apply engineering judgment to real-world machine learning engineering scenarios.

What We Re Looking For

Strong experience in machine learning engineering.

Strong experience building production ML systems, model deployment infrastructure, LLM applications, or intelligent software products.

Strong experience using coding agents and developer productivity tools.

Ability to evaluate model-generated machine learning implementations and technical tradeoffs.

Strong experience deploying machine learning systems to production environments.