GPU Architecture & AI/ML Engineer - IIT or NIT Freshers

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Hardware Engineering

General Summary:

Qualcomm graphics is the best in the mobile GPU world with the best perf/watt, perf/area and in raw performance. The GPU team has well established RnD teams from Architecture and Design to Post Silicon Validation and Functional Debug in Bangalore. The team delivers on products from the Snapdragon 800 series to the low tier 200 series. You will be joining a successful engineering department whose deliveries can be found in billions of smartphones, wearables.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience.
OR
Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.
OR
PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.

Experience: 0–3 Years

Eligibility: Fresh graduates and early-career engineers from Tier 1 and Tier 2 engineering institutes

Education: B.Tech / M.Tech in Computer Science, ECE, Electrical Engineering, Computer Engineering, or related disciplines

Role Overview

Qualcomm's GPU team is looking for highly motivated fresh graduates and early-career engineers interested in next-generation GPU, AI/ML, computer architecture, and high-performance computing technologies.

You will work alongside architecture, design, software, and validation teams on performance analysis, system-level debugging, research, automation, and development of future computing platforms.

Key Responsibilities

• Work on next-generation GPU and compute architectures.
• Contribute to architecture analysis, performance studies, validation, and debugging.
• Investigate complex hardware/software and system-level issues and perform root-cause analysis.
• Develop tools, automation, and AI-assisted engineering workflows.
• Collaborate with architecture, design, software, and validation teams.
• Research and prototype innovative solutions for future GPU and computing platforms.

Required Skills

• Strong fundamentals in Computer Architecture and Computer Organization.
• Good understanding of Operating Systems and Memory Systems.
• Strong programming skills in C/C++.
• Good knowledge of Data Structures and Algorithms.
• Basic understanding of AI/ML concepts.
• Strong analytical and problem-solving abilities.
• Ability to quickly understand complex hardware/software systems.

Good to Have

• Exposure to GPU Architecture and Parallel Computing.
• Knowledge of CUDA, OpenCL, or SYCL.
• Understanding of High-Performance Computing (HPC), accelerators, or heterogeneous computing.
• Academic/research projects involving Computer Architecture, GPU, AI/ML, Systems, or HPC.
• Research publications, patents, open-source contributions, or strong technical projects are an advantage.

Candidate Profile

We are particularly interested in candidates with:

• Strong academic and technical fundamentals.
• Genuine interest in GPU, AI, and emerging computing architectures.
• Research aptitude and strong problem-solving skills.
• Relevant academic projects, internships, publications, or technical contributions.

Freshers from Tier 1 and Tier 2 institutes with strong fundamentals and relevant academic/project exposure are encouraged to apply.

Key Screening Areas:

Must Have: Computer Architecture + C/C++ + strong problem-solving + good academic/project background.

Added Advantage: GPU Architecture, CUDA/OpenCL/SYCL, AI/ML, HPC, publications, or significant research projects.

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