Part-time remote work for ML researchers who also write a lot of code. With a master's or PhD behind you, you implement and change models, build reproducible training and inference workflows, and debug the hard failures. About 15 hours a week, when you want.
What you will do
- Create, solve, review and validate hard machine learning engineering tasks.
- Implement or change models and build reproducible training or inference workflows.
- Optimize memory or throughput and debug numerical or system-level failures.
- Check that each implementation meets objective correctness and performance requirements.
- Build data pipelines, evaluation systems and numerical methods with Python and command-line tools.
What you need
- A master's degree 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 with coding agents in your workflow. Equivalent tools may count if you show directly relevant depth.
Experience at an established tech company, lab, research organization or other recognized engineering setting 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 specs. The listed rate is $60-120/hr, and the time a task takes depends on your experience and workflow. Minimum submission requirements apply.
How applying works
- Apply and answer the screening questions.
- Complete an AI interview of about 30 minutes.
- Wait for the hiring manager review.
The listing says roles are usually filled within 48 hours. If you are selected, you are expected to start your first task within 24-48 hours of finishing onboarding.
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