Senior CUDA Engineer

Tekskills Inc.; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Tekskills Inc. is seeking a Senior CUDA Engineer to develop and optimize GPU kernels and advanced matrix operations in a CUDA-based stack. You will work closely with NVIDIA libraries and deep learning frameworks to deliver scalable performance.

The role emphasizes strong C++ expertise, kernel design for large-scale GEMM/SpMM workloads, and seamless integration with Python-based orchestration. On-site in Lucknow, immediate notice period preferred.

Qualifications

• Develop and optimize GPU compute kernels using CUDA and NVIDIA libraries.
• Tune high-performance matrix operations using cuBLAS, cuBLASLt, CUTLASS, cuSPARSE.
• Profile and optimize performance with Nsight Compute and Nsight Systems.

Responsibilities

• Design batch grouped execution flows for large-scale GEMM/SpMM workloads.
• Optimize memory layouts and data movement; tune kernel launches for throughput.
• Integrate with Python orchestration layers (PyBind11, PyTorch extensions).

Skills

GPU acceleration

CUDA programming

C++

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.