Remote MLOps Engineer for GenAI & LLM Infra

Mercor; Miami (FL); Remote; USD 120,000 - 210,000; Full time

Job summary

Mercor is seeking a hands-on ML systems engineer for a fully remote role. You will work on foundational AI model infrastructure, including kernels, profiling, and inference serving, collaborating with cross-functional teams to improve training and deployment performance.

You should have 2+ years in ML systems or accelerator engineering, with hands-on experience in JAX/PyTorch, and familiarity with modern accelerators like TPU and CUDA-based stacks. The role is 40 hours per week, globally remote.

Qualifications

• 2+ years of hands-on professional experience in ML systems, ML infrastructure, model serving, or accelerator performance engineering.
• Experience in writing or optimizing custom kernels (Pallas, Triton, CUDA, CUTLASS).
• Production experience with JAX and/or PyTorch; knowledge of distributed training and compiler/graph-level work.

Responsibilities

• Design tasks across kernels, profiling, debugging and inference serving; address frontier model failure modes on accelerator code.
• Guide research and engineering teams to improve AI model performance on ML systems, compilers and training infra.
• Evaluate ML systems tasks and provide clear technical feedback; write robust rubrics for kernel optimization and serving throughput.

Skills

ML systems experience

Accelerator performance engineering

JAX/PyTorch experience

Kernel optimization

Tools

JAX

XLA

TPU

CUDA/CUTLASS

Job description

Mercor is seeking a hands-on ML systems engineer for a fully remote role. You will work on foundational AI model infrastructure, including kernels, profiling, and inference serving, collaborating with cross-functional teams to improve training and deployment performance.

You should have 2+ years in ML systems or accelerator engineering, with hands-on experience in JAX/PyTorch, and familiarity with modern accelerators like TPU and CUDA-based stacks. The role is 40 hours per week, globally remote.