About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .
Position: JAX Expert Type: Contract Compensation: $70–$110/hour Location: Remote Commitment: 40 hours/week
Role Responsibilities
- Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps , training infrastructure, and ML framework-level topics .
- Design challenging, domain-relevant tasks and write accurate, well-structured solutions to MLOps and ML systems problems.
- Evaluate MLOps tasks and solutions and provide clear, written technical feedback.
- Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks.
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
Qualifications
Must-Have
- 2+ years of dedicated professional experience in ML infrastructure , MLOps , or ML systems engineering at a recognized, top-tier organization.
- Hands-on production experience with JAX at scale.
- Experience writing or optimizing custom GPU kernels using Pallas or Triton .
- Demonstrable career progression.
- Ability to engage reliably for at least 40 hours/week during weekdays.
- Strong written communication skills and the ability to explain complex technical decisions clearly.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check: https://talent.docs. mercor .com/welcome
- For any help or support, reach out to: support@ mercor .com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas