GenAI ML Systems Engineer & AI Trainer

Obsidian; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Cincinnatus LLC is seeking an MLOps Engineer to join a cutting-edge GenAI team, working on foundational AI model infrastructure and high-throughput inference serving. The role emphasizes hands-on ML systems work, GPU kernel optimization, and rigorous evaluation of ML solutions.

The position is a 40-hour, full-time engagement through Cincinnatus with potential placement at a leading AI Lab. Strong communication and cross-team collaboration are essential for success.

Qualifications

• 2+ years of hands-on professional experience in ML systems, ML infrastructure, model serving, or GPU and accelerator performance engineering.
• Experience in at least one: GPU kernels, profiling, debugging distributed workloads, or serving LLMs at scale.
• Working production experience with JAX and/or PyTorch; framework-level depth is a strong plus.
• Familiarity with modern accelerators and throughput/latency trade-offs.
• Ability to engage reliably for at least 40 hours/week.
• Strong written communication skills.

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

GPU kernels

Profiling tools

PyTorch/JAX

Job description

Cincinnatus LLC is seeking an MLOps Engineer to join a cutting-edge GenAI team, working on foundational AI model infrastructure and high-throughput inference serving. The role emphasizes hands-on ML systems work, GPU kernel optimization, and rigorous evaluation of ML solutions.

The position is a 40-hour, full-time engagement through Cincinnatus with potential placement at a leading AI Lab. Strong communication and cross-team collaboration are essential for success.