Location: Noida or Bengaluru

About the Role

Every millisecond of idle GPU time costs us money, and you're the person who gets rid of it. As a Kernel Engineer, you'll write and optimize the low-level CUDA and Triton kernels that determine how quick our training and inference actually run — the kind of close-to-the-metal work that most companies simply can't hire for, because there aren't many people who do it well.

What You'll Do
Write and optimize CUDA/Triton kernels for training and inference workloads across our systems and models
Profile GPU workloads and eliminate memory-bandwidth and compute bottlenecks that generic frameworks leave on the table
Implement quantization and mixed-precision kernels (FP8/INT4) that materially cut inference cost
Work directly with runtime engineering teams to get kernel-level wins into production quickly
Track recent GPU architectures as they ship and adapt our kernels to take advantage of them





What You'll Bring
8+ years of experience in systems, GPU, or performance engineering
Robust, hands-on experience writing CUDA or Triton kernels
Solid understanding of GPU microarchitecture and memory-bandwidth-bound optimization
Proficiency in C++ and a systems-level, performance-first mindset
Comfort profiling and debugging at the level of individual GPU instructions

Education

B.Tech or M.Tech in Computer Science, Electrical Engineering, or Physics, from a Tier-1 institution.

Nice to Have
PTX/SASS-level optimization experience
A background at a chip company, EDA vendor, or GPU/accelerator software team — this transfers unusually well to this role even without direct ML experience
Exposure to quantization or low-precision inference work

📌 Kernel Engineer Bengaluru
🏢 HCLTech
📍 Bengaluru