Coding-heavy contract work for ML engineers with a Master's or PhD. You build and fix models, training and inference workflows, and numerical code, then prove they meet clear correctness and performance targets. About 15 hours a week, on the days and hours you pick.
What you will do
- Create, solve, review and validate hard ML engineering tasks.
- Implement or modify models, data pipelines, evaluation systems and numerical methods.
- Build reproducible training or inference workflows with Python and command-line tools.
- Optimize memory or throughput, debug numerical and system-level failures, and check that the result meets objective correctness and performance requirements.
What you need
- A Master's or PhD in Computer Science, Machine Learning, AI, Applied Mathematics, Statistics, Engineering or a closely related quantitative field.
- Strong professional or research experience in machine learning.
- Practical skill with Python and experience using coding agents in your workflow. Equivalent tools may be considered with directly relevant depth.
- Experience at an established tech company, AI lab, research organization or similar engineering environment counts strongly in your favor. Exceptional open-source or academic work may also qualify.
How pay works
Pay is output-based: you are paid per task that meets the project specifications, at a listed rate of $60-120/hr. How long a task takes depends on your experience and workflow. Minimum submission requirements apply.
How applying works
- Apply and answer the screening questions.
- Take an AI interview, about 30 minutes.
- Pass the hiring manager review.
Roles are typically filled within 48 hours. If selected, you are expected to start your first task within 24-48 hours of finishing onboarding.
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