GPU AI Performance Engineer

MaC VC; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Qualcomm India Private Limited is seeking a GPU AI Performance Engineer to design, optimize, and accelerate AI workloads on GPU platforms. The role spans from model graphs and inference runtimes down to GPU kernels and compiler IR, with a focus on performance, memory efficiency, and scalability of modern AI models, including LLMs and transformers.

You will analyze architectures, identify bottlenecks, and collaborate with hardware, software, and ML teams to drive architectural and algorithmic

Qualifications

• Bachelor's degree or above in Engineering/CS/IS with substantial Systems Eng experience.
• 5+ years (PhD: 4+ years) in Systems Eng or related field.
• Experience in GPU/CPU architecture and AI workloads.

Responsibilities

• Analyze and optimize GPU architecture for AI workloads performance.
• Work across the AI stack from models to GPU kernels and compilers.
• Collaborate with hardware, software and ML teams to identify bottlenecks and optimizations.
• Analyze AI workload behavior across GPU generations and platforms.
• Contribute to architectural trade-off studies and roadmap data-driven decisions.

Skills

Python

C++

ML frameworks

Verilog/SystemVerilog

Assembly

CUDA

OpenCL

Perl

Model deployment/runtime

Education

Bachelor's degree (Engineering/CS/IS)

Master's degree (Engineering/CS/IS)

PhD (Engineering/CS/IS)

Tools

Triton

TTIR

TTGIR

GPU compiler pipelines

CUDA

OpenCL

Job description

Company

Qualcomm India Private Limited

Job Area

Engineering Group, Engineering Group > Systems Engineering

General Summary

We are looking for a GPU AI Performance Engineer to help design, optimize, and accelerate AI workloads on GPU-based platforms. This role focuses on improving the performance, memory efficiency, and scalability of modern AI models — especially LLMs, transformer workloads, MoE models, and computer vision pipelines — by working across the stack from model architecture to compiler/runtime integration and low-level kernel optimization.

Responsibilities

• Analyze and evaluate GPU architecture/microarchitecture for performance optimizations of AI workloads
• Work across the AI stack, from model graphs and inference runtimes down to GPU kernels and compiler IR
• Collaborate with hardware, software, and ML teams to identify performance bottlenecks and propose architectural or algorithmic optimizations
• Analyze AI workload characteristics and correlate their behavior across different GPU generations
• Contribute to architectural trade-off studies and influence GPU roadmap decisions with data-driven insights

Preferred Skills

• Strong understanding of CPU/GPU architecture
• Experience in Python, C++, and ML frameworks (e.g., TensorFlow, PyTorch)
• Skills: C/C++ Programming Language, Scripting (Python/Perl), Assembly, Verilog/SystemVerilog
• Familiarity with AI inference runtimes and deployment stacks for model compilation, optimization, and execution on GPU/accelerator platforms
• Good understanding of common neural network layers and operations, including what they do and how they affect model behavior and performance

Nice To Have

• Experience with LLM inference engines such as llama.cpp
• Exposure to Triton, TTIR, TTGIR, or GPU compiler pipelines
• Knowledge of quantization formats and tradeoffs
• Understanding of MoE architectures
• Experience with GPU driver and compiler development
• Experience with OpenCL or Cuda development

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
• Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
• PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.

Applicants

Qualcomm is an equal opportunity employer.

If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process.

You may e-mail [e-mail] or call Qualcomm's toll-free number found here.

Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process.

Qualcomm is also committed to making our workplace accessible for individuals with disabilities.

(Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.