GPU Engineer

MulticoreWare, Inc.; Chennai District; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

MulticoreWare is seeking an experienced GPU Programming Engineer to develop, optimize, and deploy GPU-accelerated solutions for high-performance deep learning workloads. The role focuses on CUDA, HIP, or OpenCL across one or more platforms, interfacing with DL systems and HPC workloads.

The ideal candidate has 2+ years in GPU programming, strong CUDA/OpenCL knowledge, and solid C/C++ under Linux. Bengaluru location, with a path toward performance-driven software engineering at scale.

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.
• Strong understanding of GPU architecture, memory hierarchy, shared memory, bank conflicts and parallel programming models.

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.

Skills

CUDA

OpenCL

C/C++

Linux

Nsight

Education

Bachelor's or Master's in CS/EE

Tools

Nsight

rocprof

Perfetto

Job description

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 seeking an experienced GPU Programming Engineer to join our team. In this role, youwill 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 theintersection of parallel computing, performance tuning, and DL system integration

Location : Bengaluru

Key Responsibilities

• Develop, optimize, and maintain GPU-accelerated components for deep learningpipelines using frameworks such as CUDA, HIP, or OpenCL
• Analyse and improve GPU kernel performance through profiling, benchmarking, andresource optimization.
• Optimize memory access, compute, throughput, and kernel execution to improve overallsystem performance on the target GPUs.
• Port existing CPU-based implementations to GPU platforms while ensuring correctnessand performance scalability.
• Work closely with system architects, software engineers, and domain experts tointegrate GPU-accelerated solutions.

Required Qualifications

• Bachelor's or master's degree in computer science, Electrical Engineering, or a relatedfield.
• 2+ years of hands-on experience in GPU programming, preferably using CUDA, or otherGPU APIs like HIP, OpenCL etc.,
• Strong understanding of GPU architecture, memory hierarchy, shared memory, bankconflicts 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