Senior CUDA Engineer

Tekskills Inc.; Chennai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Tekskills Inc. in Lucknow, UP, seeks a Senior CUDA Engineer to develop and optimize GPU kernels, leveraging CUDA, cuBLAS, and NVIDIA libraries. The role focuses on high-performance matrix ops, profiling, and integration with Python-based layers.

The ideal candidate has 6–8 years of experience with C++ and CUDA, and will work on tensor cores, CUDA libraries, and PyTorch extensions in a fast-paced environment.

Qualifications

• Experience in developing GPU kernels using CUDA for high-performance computation.
• Strong background in C++ programming and GPU-accelerated workflows.
• Familiarity with NVIDIA libraries (cuBLAS/cuSPARSE) and depth in mixed-precision computation.

Responsibilities

• Develop and optimize GPU compute kernels using CUDA, Tensor Cores, and NVIDIA libraries.
• Implement and tune high-performance matrix operations using cuBLAS cuBLASLt, CUTLASS, and cuSPARSE.
• Design batch grouped execution flows for large-scale GEMM/SpMM workloads; optimize memory layouts and kernel launches.
• Conduct profiling and performance tuning using Nsight Compute and Nsight Systems.
• Build clean and stable CC APIs and integrate with Python (PyBind11, PyTorch extensions).
• Ensure numerical correctness, mixed-precision stability, and robust error handling.

Skills

C++

CUDA

GPU acceleration

Deep learning inference

Tools

cuBLAS

cuBLASLt

CUTLASS

cuSPARSE

Nsight Compute

Nsight Systems

PyBind11

PyTorch extensions

Job description

Job Title: Senior CUDA Engineer

Location: Lucknow, UP

Skills Required: C++
Experience: 6 to 8 Years

Notice Period: Immediate and 15 Days

Job Description:

• Develop and optimize GPU compute kernels using CUDA, Tensor Cores, and NVIDIA libraries Implement and tune high-performance matrix operations using cuBLAScuBLASLt, CUTLASS, and cuSPARSE
• Design batch grouped execution flows for large-scale GEMM SpMM workloads Optimize memory layouts, data movement, and kernel launch efficiency
• Conduct profiling and performance tuning using Nsight Compute Nsight Systems
• Build clean and stable CC APIs and integrate with Python (PyBind11 PyTorch extensions)
• Ensure numerical correctness, mixed-precision stability, and robust error handling

Essential Skills:

• We are seeking a highly skilled Senior CCUDA Engineer with strong experience in GPU-accelerated computation and deep learning inference.
• The role involves developing high-performance GPU kernels, optimizing large-scale matrix operations, and integrating with Python-based orchestration layers.