The unified AI inference stack - from custom GPU kernels to production cloud serving on NVIDIA and AMD. 2x performance. Top open models. Open source stack. Backed by General Catalyst, Greylock and GV.
About the role
We are seeking a Senior AI Kernel Engineer to lead the design and optimization of high-performance kernels for large-scale AI inference on GPUs and emerging custom accelerators. In this role, you will own performance-critical paths, drive architectural decisions, and turn complex AI workloads into highly optimized implementations that run efficiently at scale.
What they're looking for
- 5+ years of experience in performance-critical systems or kernel development (or equivalent depth of expertise)
- Strong proficiency in C/C++ and low-level programming
- Extensive hands-on experience with GPU kernel programming (CUDA, HIP, or equivalent)
- Deep understanding of GPU architecture , including memory hierarchies, synchronization, and execution models
- Proven track record of delivering measurable performance improvements in production systems
- Strong problem-solving skills and ability to work independently on complex, ambiguous performance challenges
More about this role
At Modular, a Qualcomm company , we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about our culture and careers to understand how we work and what we value.
We are seeking a Senior AI Kernel Engineer to lead the design and optimization of high-performance kernels for large-scale AI inference on GPUs and emerging custom accelerators. In this role, you will own performance-critical paths, drive architectural decisions, and turn complex AI workloads into highly optimized implementations that run efficiently at scale.
You will work at the intersection of hardware, compilers, and AI systems, collaborating closely with compiler, runtime, model, and...
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