At Pareto AI, we collaborate with top AI companies including Google DeepMind, Amazon, Stanford Labs, and Anthropic to run cutting-edge research projects. We're currently seeking experienced Machine Learning Engineers with deep expertise in open-source ML tools for an exciting research initiative.

The Project

We're building a comprehensive set of programmatically verifiable tasks for a variety of open-source ML tools, including Apache Airflow , Feast , H2O AutoML , and MLflow . This project sits at the intersection of machine learning tooling and automated evaluation systems.

Your Role

As a subject-matter expert, you'll be responsible for:

• Designing Tasks : Create meaningful, realistic tasks that can be completed within your area of expertise (Apache Airflow, Feast, H2O AutoML, or MLflow), covering various use cases and difficulty levels
• Building Evaluation Scripts : Develop robust scripts that automatically verify whether an AI model has successfully completed each task
• Ensuring Quality : Design tasks that are clear, unambiguous, and programmatically verifiable
• Documentation : Document task specifications, expected outcomes, and evaluation criteria

What We're Looking For:

Ideal:

• Experience with multiple open-source ML tools from the list above
• Background in MLOps, data engineering, or ML infrastructure
• Understanding of automated testing and verification systems
• Experience with production ML systems and workflows
• Contributions to open-source projects

Project Details:

• Duration : 2-3 months (project-based contract)
• Commitment : 30+ hours per week required (40+ hours preferred) Availability Mon-Fri at least 1 hour per day from 5am - 2pm PST (5 hours per week).
• Compensation : $80-100 USD per hour
• Work Style : Remote, flexible hours
• Start Date : As soon as possible

We're grateful for your interest and look forward to potentially working together!