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: MLOps Engineer (JAX, PyTorch, Pallas/Triton) 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 and 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+ yearsof dedicated professional experience in ML infrastructure, MLOps, or ML systems engineeringat a recognized, top-tier organization.
- Hands-on production experience with JAXand/or PyTorchat scale.
- Experience writing or optimizing custom GPU kernelsusing Pallas (JAX)or Triton.
- Demonstrable career progression.
- Ability to engage reliably for at least 40 hours/weekduring 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:
- For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas
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