SDE IV - GPU Engineer (AI)

TL;DR

SDE IV - GPU Engineer (AI): Leading design and optimization efforts across the GPU inference stack for Stable Diffusion, multimodal transformers, and video generation models with an accent on architecting high-performance inference runtimes, kernel dispatchers, and memory planners. Focus on driving multi-GPU parallelism strategies, establishing company-wide GPU optimization standards, and collaborating with research for scalable implementations of novel architectures.

Location: Onsite in Bangalore, India

Company

hirify.global AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, backed by Google, Jio Platforms, and Mithril Capital.

What you will do

• Architect high-performance inference runtimes, kernel dispatchers, and memory planners for large diffusion and transformer workloads.
• Lead investigations into cross-GPU performance bottlenecks and scheduling inefficiencies.
• Drive multi-GPU parallelism strategies including model, pipeline, and tensor parallelization.
• Establish company-wide GPU optimization standards, tooling, and SLIs.
• Collaborate with research to design scalable implementations of novel architectures.
• Mentor engineers in profiling, tuning, and low-level optimization.

Requirements

• 5+ years in high-performance computing, GPU runtime systems, or ML infrastructure.
• Proven expertise in CUDA / Triton / C++, with deep understanding of GPU scheduling, occupancy, register usage, and tensor cores.
• Experience building and maintaining distributed inference or training systems.
• Ability to design abstractions balancing flexibility and performance.
• Strong knowledge of NCCL, NVLink, PCIe, and interconnects.
• Familiar with profiling automation and performance dashboards.
• Excellent technical leadership and mentoring capabilities.

Nice to have

• Background in compiler-aided optimization (TVM, XLA, MLIR, Triton).
• Experience tuning Stable Diffusion or transformer inference pipelines.
• Exposure to heterogeneous compute backends (AMD ROCm, TPU, ASICs).
• Experience working with hardware–software co-design initiatives.
• Open-source or research contributions in GPU optimization.

Culture & Benefits

• Flexible work arrangement to inspire work-life balance.
• Salad bar and nutritious meals provided for healthy lifestyle.
• Fitness events and a play arena for sports enthusiasts.