We are seeking an experienced GPU Programming Engineer to join our team. In this role, you will focus on developing, optimising, and deploying GPU-accelerated solutions for highperformance deep learning workloads. The ideal candidate has strong expertise in GPU programming across one or more platforms. (e.g., NVIDIA CUDA or AMD ROCm/HIP, or OpenCL) and is comfortable working at the intersection of parallel computing, performance tuning, and DL system integration

Location : Bengaluru

Key Responsibilities

- Develop, optimize, and maintain GPU-accelerated components for deep learning pipelines using frameworks such as CUDA, HIP, or OpenCL
- Analyse and improve GPU kernel performance through profiling, benchmarking, and resource optimization.
- Optimize memory access, compute, throughput, and kernel execution to improve overall system performance on the target GPUs.
- Port existing CPU-based implementations to GPU platforms while ensuring correctness and performance scalability.
- Work closely with system architects, software engineers,



and domain experts to integrate GPU-accelerated solutions.

Required Qualifications

- Bachelor's or master's degree in computer science, Electrical Engineering, or a related field.
- 2+ years of hands-on experience in GPU programming, preferably using CUDA, or other GPU APIs like HIP, OpenCL etc.,
- Solid understanding of GPU architecture, memory hierarchy, shared memory, bank conflicts and parallel programming models.
- Proficiency in C/C++ and hands-on experience developing on Linux-based systems.
- Familiarity with profiling and tuning tools such as Nsight, rocprof, or Perfetto

Good to have skills in addition to GPU :
- Knowledge and Experience in SIMD Programming
- Good understanding of NN Operators & Hands-on experience with PT, TF, Tensor RT.
- Exposure to DL Concepts like Quantization, Pruning etc.,
- Experience in working with High Performance Compute (HPC) Systems

📌 GPU Engineer (Chennai)
🏢 MulticoreWare
📍 Chennai