Job highlights

- Bachelors or masters degree in Computer Science,Electrical Engineering,or a related field
- . Technical Skills (Must haves): .
- Preferred Qualifications (Optional): . Additional experience in GPU performance engineering,deep learning system optimization, or heterogeneous computing would be advantageous

":" We are looking for an experienced GPU Programming Engineer to develop, optimize, and deploy GPU-accelerated solutions for high-performance deep learning workloads. The role focuses on GPU programming, parallel computing, performance tuning, and deep learning system integration across platforms such as NVIDIA CUDA, AMD ROCm/HIP, and OpenCL.

**Responsibilities:

- Develop, optimize, and maintain GPU-accelerated components for deep learning pipelines using CUDA, HIP, or OpenCL.
- Analyze 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 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.

Requirements

**Education:

Bachelors or masters degree in Computer Science, Electrical Engineering,



or a related field.

**Technical Skills (Must haves):

**

- 2+ years of hands-on experience in GPU programming, preferably using CUDA, HIP, OpenCL, or similar GPU APIs.
- Strong 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.

**Need to have (Can be bridged):
- Knowledge and experience in SIMD programming.
- Good understanding of neural network (NN) operators and hands-on experience with PyTorch, TensorFlow, or TensorRT.

**Valuable to have (Not essential):
- Exposure to deep learning concepts such as quantization and pruning.
- Experience working with High Performance Computing (HPC) systems.

**Preferred Qualifications (Optional):

Additional experience in GPU performance engineering, deep learning system optimization, or heterogeneous computing would be advantageous.

",

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 GPU Engineer (Chennai)
🏢 MulticoreWare
📍 Chennai