MLOps Engineer, LLM Performance (Kernels, Profiling, Serving)
About this role
Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.
1\. Overview
Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking MLOps and ML systems engineers with hands-on experience in large language model infrastructure across any of four areas: accelerator kernel programming, performance profiling and trace analysis, debugging accelerated and distributed workloads, and high-throughput inference serving. Experience with JAX, XLA or TPUs is especially valuable. This role involves AI model training and evaluation work, including writing and assessing ML systems tasks and solutions to generate high-quality training data for frontier AI systems.
This is a fully remote role open to candidates worldwide. Depending on where you are based, your engagement will be arranged through Cincinnatus LLC or one of its trusted employer-of-record partners in your country, with the opportunity to be placed at a leading AI lab as part of their extended workforce. This is a 40-hour full-time engagement, with no conflicts/no other engagements.
2\. Key Responsibilities
- Design challenging tasks across kernels, profiling, debugging and inference serving, including adversarial problems that expose where frontier models fail on accelerator code (for example Pallas kernels on TPU), and write accurate, well-structured solutions to them.
- 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, and 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.
3\. Core Qualifications
- 2+ years of hands-on professional experience in ML systems, ML infrastructure, model serving, or accelerator performance engineering. This is a hands-on systems role rather than an applied modelling or data science one.
- Practical experience in at least one of the following, with more than one a strong plus: writing or optimizing custom kernels (Pallas, Triton, CUDA, CUTLASS); performance profiling and trace analysis (JAX/XLA profiler, Kineto, torch.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. Framework-level depth is a strong plus: custom operators, sharding and distributed training (pjit/shard_map, FSDP, Megatron, MaxText), or compiler and graph-level work (XLA/StableHLO, torch.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.
About Cincinnatus LLC:
Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and engage highly skilled professionals for contingent and contract-based opportunities. Working directly or through local employer-of-record partners, Cincinnatus handles the employment or contracting relationship, payroll, benefits where applicable, and compliance in each country, while placing professionals directly within client teams to work on high-impact initiatives.
Equal Employment Opportunity:
Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic.
Details
- Pay: $90 to $120/hr
- Company: Mercor
- Location: Remote
- Eligible locations: Worldwide (no restriction)
- Platform: Mercor
Frequently asked questions
How much does the MLOps Engineer, LLM Performance (Kernels, Profiling, Serving) role pay?
Mercor lists this MLOps Engineer, LLM Performance (Kernels, Profiling, Serving) position at $90 to $120/hr. Pay is set by Mercor and your exact offer depends on your experience and the scope of the work.
Is the MLOps Engineer, LLM Performance (Kernels, Profiling, Serving) role remote, and can I work from home?
Yes. Mercor lists this MLOps Engineer, LLM Performance (Kernels, Profiling, Serving) position as fully remote, so you can work from home or anywhere with a reliable computer and internet connection.
Is MLOps Engineer, LLM Performance (Kernels, Profiling, Serving) full time or part time?
Mercor lists this as a contractor remote role. Full details are in the role description above.
Which countries can apply for MLOps Engineer, LLM Performance (Kernels, Profiling, Serving)?
Mercor lists this role with no country restriction. Check the Mercor listing for current requirements before applying.
Do I need experience to apply for MLOps Engineer, LLM Performance (Kernels, Profiling, Serving)?
The requirements are listed in the role description above. Mercor screens applicants through its own process, and relevant skills or credentials strengthen your application.
How do I apply for the MLOps Engineer, LLM Performance (Kernels, Profiling, Serving) role, and is it legit?
Use the apply button on this page to go straight to the official Mercor listing. Mercor is a real hiring marketplace and applying is free. No legitimate employer charges you to apply.
Stay Updated on Roles Like This
Subscribe to receive fresh openings aligned with AI Training & Evaluation and AI training roles across Mercor and JobHub by NeonLabs