Machine Learning Engineer (Remote | $60–$120/hr)

Data Scientist Position: Data Scientist Type: Contractor Compensation: $60–$120/hour Location: Global, Fully Remote About the Opportunity We’re looking for data scientists, machine learning practitioners, and applied mathematics experts with experience in competitive data science, including platforms such as Kaggle and DrivenData. In this role, you’ll use your competition experience, mathematical reasoning, and programming skills to create challenging tasks for evaluating AI coding agents. You’ll develop reproducible environments, implement verified reference solutions, and establish reliable tests to assess the correctness of AI-generated solutions. Key Responsibilities • Build reproducible environments, prepare relevant datasets and dependencies, and implement reference solutions. • Develop tests and evaluation criteria to distinguish correct solutions from incomplete or flawed approaches. • Run AI coding agents against tasks, investigate failures, and refine tasks based on observed behavior. • Identify implementation errors, flawed assumptions, data leakage, and other issues affecting correctness. • Document task requirements, solution reasoning, and verification steps clearly. Required Qualifications • Demonstrated experience in data science, machine learning, quantitative modeling, or relevant research competitions. • Strong mathematical reasoning and problem-solving skills. • Practical programming skills to implement and verify solutions independently. • A clear understanding of the methods used and the ability to assess solution correctness. Preferred Qualifications • Strong Python programming experience. • Experience with testing, debugging, and working with unfamiliar code. • Experience with competitive data science platforms such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench. Compensation • Hourly rate: $60–$120. • Contractor engagement with an expected commitment of approximately 15 hours per week. Additional Details • Work Arrangement: Fully remote, open globally. • Schedule: Flexible. Choose your preferred working hours and days, including weekends. • Engagement: Approximately 15 hours per week.