[Hiring] MLOps Engineer @Mercor

Role Description

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, 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

• 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, torch.profiler).
• Working production experience with JAX and/or PyTorch.
• Familiarity with modern accelerators such as A100, H100, or TPU.
• Strong written communication skills.

Requirements

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

Application Process

• 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: [email protected]
• Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.