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 fast 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 new 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