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:

• PhD student or recent PhD graduate in Computer Science, Machine Learning, or related field
• Deep hands-on experience with at least one of the following:
• Apache Airflow
  • workflow orchestration and data pipeline management
• Feast
  • feature store for ML feature management
• H2O AutoML
  • automated machine learning and model training
• MLflow
  • experiment tracking, model registry, and deployment
• Proficiency in Python and script development
• Experience designing ML tasks, benchmarks, or evaluation systems
• Strong analytical and problem-solving skills

Ideal:

• Experience with multiple open-source ML tools from the list above
• Background in ML evaluation methodologies
• Understanding of automated testing and verification systems
• Prior research or industry experience with MLOps, data orchestration, or AutoML systems

Project Details

• Duration : 2-3 months (project-based contract)
• Commitment : 30+ hours per week required (40+ hours preferred). Availability Mon-Fri for at least one hour per day between 5am and 2pm Pacific Time
• 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!