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