AI Systems Engineer

Because this field is new, we don’t expect years of experience.

We’re looking for engineers with great systems intuition, intellectual curiosity, and a strong desire to embrace AI-driven engineering.

Strong signals include:

• Experience with AI inference, distributed serving, model optimization, and related topics.
• Hands-on with vLLM, PyTorch, Triton inference server, Ray Serve, or other inference frameworks
• Experience with GPU optimization, kernel design, CUDA programming, and low-level systems performance engineering
• Strong Python and PyTorch fundamentals
• Comfort in building large-scale, high-performance distributed systems
• PhD or equivalent experience (PhD or equivalent + ~5 years is a good sweet spot)
• Dislike for rigid bureaucratic engineering processes, but appreciation for disciplined engineering rigor.

Glia AI?

• Strong pedigree: Work alongside a team of renowned experts in AI-driven systems.
• Massive impact: Our technology has demonstrated the ability to achieve significant improvements in long-running engineering research and design tasks spanning performance engineering, model pipeline development, and cost optimization..
• Robust financials: Our seed round ($13.5M) closed in September 2025; we’re backed by top-tier VC firms ( Pillar , E14 , and Neotribe ), as well as luminaries like Jeff Dean , Ion Stoica , Aparna Chennapragada , Nick McKeown , Srinivas Narayanan , and more. We are in the midst of multiple paid PoCs with marquee customers.
• Solving hard problems: We are solving the fundamental bottlenecks of the AI revolution: quality, performance, and cost.