MLOps Engineer (JAX, PyTorch, Pallas/Triton) | $70-$110/hr Remote
Overview
This role places you inside a top-tier AI lab's generative AI team, where you'll help build and improve foundational large language models. As an MLOps Engineer, you'll focus on training infrastructure, framework-level optimization, and creating high-quality training data by designing and evaluating technical tasks. You'll work hands-on with JAX, PyTorch, and Pallas/Triton for kernel-level programming—and your work will directly shape the next generation of frontier AI systems. This is a W-2 position through Cincinnatus LLC, offering a 40-hour-per-week remote engagement with no other projects allowed.
What You'll Do5
- 1Collaborate with research and engineering teams to identify knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework topics.
- 2Design challenging, domain-specific tasks and write clear, well-structured solutions for MLOps and ML systems engineering problems.
- 3Evaluate MLOps tasks and solutions, providing concise written technical feedback to contributors.
- 4Develop comprehensive rubrics and evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across a range of tasks.
- 5Work with other subject matter experts to maintain consistency, accuracy, and quality in training data.
Requirements6
- 1At least 2 years of hands-on professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized top-tier organization.
- 2Proven production experience using JAX and/or PyTorch at scale.
- 3Hands-on experience writing or optimizing custom GPU kernels with Pallas or Triton.
- 4A track record of career progression and growing technical responsibility.
- 5Ability to reliably commit to at least 40 hours per week during standard weekday hours.
- 6Strong written communication skills to explain complex technical decisions clearly.
Who Should Apply
You're an MLOps engineer who thrives at the intersection of machine learning research and production systems. You have deep experience with modern ML frameworks and enjoy getting your hands dirty with kernel-level performance. You're not just an engineer who likes to build—you also take pleasure in teaching, writing, and evaluating technical content to help AI models improve. You value consistency, have strong attention to detail, and are comfortable working independently in a remote, fast-moving environment. If you're looking to make a direct impact on cutting-edge AI models while working with a collaborative team, this is the role for you.
Salary Insight
$70.00 - $110.00 per hour on a W-2 basis, with an expected commitment of 40 hours per week.
Location
Required Skills
Application Tip
Highlight specific examples of custom GPU kernels you've written with Pallas or Triton, including any performance benchmarks or speedups you achieved. A concrete, quantifiable win will help you stand out over candidates who just list the framework.
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