ML Infrastructure Expert - Fully Remote | Up to $120/hr

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 Performance (Kernels, Profiling, Serving) Type: Contract Compensation: $90–$120/hour Location: Remote Commitment: 40 hours/week Role

Responsibilities Design challenging tasks across kernels, profiling, debugging, and inference serving. Write accurate, well-structured solutions to expose where frontier models fail on accelerator code. Guide research and engineering teams to close knowledge gaps and improve AI model performance on ML systems, compilers, and training infrastructure topics. Evaluate ML systems tasks and solutions. Provide clear written technical feedback that stands up to expert review.

Develop guidelines and detailed rubrics covering kernel optimization, profiler output interpretation, distributed systems reasoning, and serving throughput and latency trade-offs. Collaborate with other subject matter experts to keep training data consistent and accurate.

Qualifications Must-Have 2+ years of hands-on professional experience in ML systems, ML infrastructure, model serving, or accelerator performance engineering. profiler, Nsight), debugging distributed or accelerator-bound workloads, serving large language models at scale (vLLM, SGLang, TensorRT-LLM, JetStream, KV cache, paged attention, continuous batching). Working production experience with JAX and/or PyTorch. compile, MLIR).

Experience with modern accelerators such as TPU (v4 to v6e), H100, B200, Trainium or MI300, and the ability to reason about throughput, latency, and memory trade-offs. Demonstrable career progression. Ability to engage reliably for at least 40 hours/week during weekdays. Strong written communication skills and the ability to explain complex technical decisions clearly. com PS: Our team reviews applications daily.

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