MLOps Engineer, LLM Performance (Kernels, Profiling, Serving)
$90–120/hr
Remote STEM contract with Mercor, $90–120/hr. Posted Oct 22.
$90–120/hr
Apply on MercorIs this job worth applying to?
- Pay
- Above typicalTops out at $120/hr. The typical top rate across 148 priced STEM listings is $70/hr.
- Getting in
- Some screening~30 min: resume upload + 20-min AI interview. Resume showing real experience in your field.
- Steady work
- Work is patchyProjects can pause or end with little notice.
- Payout record
- Pays on timeSchedule: weekly, every Wednesday. Paid via Stripe (Wise in a few countries).
- Freshness
- RecentPosted 2w ago. Still listed on Mercor on Nov 6, 2026.
- Where you live
- Not statedThe listing names no country.
The job description
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.
How do you apply to Mercor?
Apply on Mercor
The Apply button opens this post on Mercor's own site. You apply with them, not with Rubric. Budget about 30 min: resume upload + 20-min AI interview.
Get through screening
What Mercor asks for after you apply:
- Take the recorded AI video interview (practice round available)
- Complete any role-specific assessment and the ID check
- Accept the offer and sign the contract
Start work and get paid
Pay schedule: weekly, every Wednesday. Paid via Stripe (Wise in a few countries). You're paid for the work they hand out, not a fixed salary.
Mercor also needs
- Resume showing real experience in your field
- Webcam with your full face visible for the AI interview
- Government ID
Red flags
- Red flagLong waits with no offer after passing the interview
- Red flagProjects ending abruptly with little warning
What is Mercor like to work for?
Hiring marketplace that screens professionals with an AI video interview and places them on hourly contracts training and evaluating models for AI labs.
| Advertised pay | $20–200/hr |
|---|---|
| Getting in | Some screening |
| Application takes | ~30 min: resume upload + 20-min AI interview |
| How you get paid | Weekly, every Wednesday, via Stripe (Wise in a few countries) |
| Payout record | Pays on time |
| Countries | Hires in many countries and runs its pay week on India Standard Time; Mercor keeps a list of locations it cannot onboard, and some projects are US-only. |
Most listings sit around $50–100/hr; healthcare, legal and finance roles pay the most, language and generalist roles the least.
