ML Systems Engineer - Fully Remote | Upto $120/hr

mercor · United States · $90 – $120 · posted today ago

engineering machine-learning remote jobs in united states

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About this role

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