ML Systems Engineer AI Trainer

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 DAngelo Larry Summers and Jack Dorsey.

Position: MLOps Engineer LLM Systems (Serving GPU Kernels Profiling)
Type: Contract
Compensation: $90$120/hour
Location: Remote
Commitment: 40 hours/week

Role Responsibilities

• Design challenging tasks across GPU kernels performance profiling debugging and inference serving. Write accurate well-structured solutions.
• Guide research and engineering teams to close knowledge gaps and improve AI model performance on ML systems and training infrastructure.
• Evaluate MLOps and ML systems tasks. Provide clear written technical feedback that stands up to reviewer scrutiny.
• Develop guidelines and detailed rubrics covering kernel-level optimization profiler output interpretation and serving throughput and latency trade-offs.
• Collaborate with other subject matter experts to ensure training data consistency and accuracy.

Qualifications

Must-Have

• 2 years of hands-on professional experience in ML systems ML infrastructure or GPU performance engineering.
• Practical experience in GPU kernels (e.g. CUDA Triton) or performance profiling (e.g. Kineto ).
• Working production experience with JAX and/or PyTorch.
• Familiarity with modern accelerators such as A100 H100 or TPU.
• Strong written communication skills.

Compensation & Legal

• W-2 employment with Cincinnatus LLC.
• Equal Employment Opportunity employer.

Application Process (Takes 2030 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

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PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.