GenAI MLOps Engineer for LLM Systems

Dorado; United States; Remote; USD 140,000 - 220,000; Full time

Job summary

Cincinnatus LLC is actively seeking a hands-on MLOps Engineer to join a cutting-edge GenAI team responsible for building foundational AI models and scalable inference serving. The role emphasizes GPU kernel programming, performance profiling, and distributed workloads within a high-impact AI lab setting.

The position is a 40-hour full-time engagement as an employee of record, with opportunity to be placed at a leading AI Lab as part of the extended workforce.

Qualifications

• 2+ years of hands-on professional experience in ML systems, ML infrastructure, model serving, or GPU and accelerator performance engineering.

Responsibilities

• Design challenging, domain-relevant tasks across four areas, GPU kernels, performance profiling, debugging, and inference serving, 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, training infrastructure, and framework-level topics.
• Evaluate MLOps and ML systems tasks and solutions, and provide clear, written technical feedback that stands up to reviewer scrutiny.
• Develop guidelines and detailed rubrics or evaluation frameworks covering kernel-level 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.

Skills

ML systems experience

GPU kernel programming

Performance profiling

Debugging distributed workloads

Serving LLMs at scale

Strong written communication

40 hours/week reliability

Tools

CUDA

Triton

Pallas

Kineto

torch.profiler

Nsight

XLA

JAX

PyTorch

vLLM

SGLang

TensorRT-LLM

Ray Serve

KV cache

paged attention

continuous batching

Job description

Cincinnatus LLC is actively seeking a hands-on MLOps Engineer to join a cutting-edge GenAI team responsible for building foundational AI models and scalable inference serving. The role emphasizes GPU kernel programming, performance profiling, and distributed workloads within a high-impact AI lab setting.

The position is a 40-hour full-time engagement as an employee of record, with opportunity to be placed at a leading AI Lab as part of the extended workforce.