MLOps Engineer - GPU Specialist

Mercor connects creative and technical talent with leading AI research labs. The MLOps Engineer, LLM Systems role focuses on designing and evaluating technical tasks involving GPU kernels, performance profiling, debugging, inference serving, and ML infrastructure, while creating guidelines and providing technical feedback.

What you'll do:

• 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

What they're looking for:

• 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