Job Information

- Department Name Platforms & Compilers
- Job Type Full time
- Date Opened 30/08/2026
- Industry Software Development
- Minimum Experience In Years 2
- Maximum Experience In Years 5
- City Chennai
- Province Tamil Nadu
- Country India
- Postal Code 600089

About Us

MulticoreWare is a global software solutions & products company with its HQ in San Jose, CA, USA. With worldwide offices, it serves its clients and partners in North America, EMEA and APAC regions. Started by a group of researchers, MulticoreWare has grown to serve its clients and partners on HPC & Cloud computing, GPUs, Multicore & Multithread CPUS, DSPs, FPGAs and a variety of AI hardware accelerators.

MulticoreWare was founded by a team of researchers that wanted a better way to program for heterogeneous architectures. With the advent of GPUs and the increasing prevalence of multi-core, multi-architecture platforms, our clients were struggling with the difficulties of using these platforms efficiently.

We started as a boot-strapped services company and have since expanded our portfolio to span products and services related to compilers, machine learning, video codecs, image processing and augmented/virtual reality. Our hardware expertise has also expanded with our team; we now employ experts on HPC and Cloud Computing, GPUs, DSPs, FPGAs, and mobile and embedded platforms. We specialize in accelerating software and algorithms, so if your code targets a multi-core, heterogeneous platform, we can help.

Job Description

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:

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

Requirements

Education:

Bachelor's or master's 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.
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Solid understanding of GPU architecture, memory hierarchy, shared memory, bank conflicts, and parallel programming models.
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Proficiency in C/C++ and hands-on experience developing on Linux-based systems.
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Familiarity with profiling and tuning tools such as Nsight, rocprof, or Perfetto.

Need to have (Can be bridged):

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Knowledge and experience in SIMD programming.
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Good understanding of neural network (NN) operators and hands-on experience with PyTorch, TensorFlow, or TensorRT.

Good to have (Not essential):

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Exposure to deep learning concepts such as quantization and pruning.
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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.

📌 GPU Engineer (Chennai)
🏢 MulticoreWare
📍 Chennai