AI Systems Software Engineer – Senior Engineer/Lead Senior Engineer

Overview

Design, integrate, profile and optimize system software that enables high-performance AI workloads across CPUs, GPUs, DSPs and NPUs on Snapdragon platforms, including platform software for CPU and NPU processors and their AI engines.

What you'll do

• Drive feature adoption and maximize performance on Windows AI platforms by developing system-level solutions and resolving complex integration and performance issues.
• Profile and optimize system performance, applying knowledge of advanced DSP architecture and microarchitecture-level optimizations to achieve low latency and low power.
• Collaborate with cross-functional teams (hardware, tools, and firmware) to evaluate design trade-offs and incorporate and drive adoption of features that improve performance.
• Collaborate with cross-functional and global teams to develop best-in-class, high-performance AI solutions that can be leveraged by third-party Windows application developers.
• Perform competitive benchmarking of AI tools, workflows, and state-of-the-art models across industry-leading platforms.
• Drive continuous improvements in AI model performance, efficiency, and accuracy on Windows on Snapdragon platforms.

What you'll need

• Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
• 3-7 years of experience in AI/ML application development (multiple levels of openings).
• Strong programming skills in C, C++, and Python.
• Experience architecting, designing, and implementing software frameworks for complex heterogeneous or multi-processor systems.
• Good understanding of the end-to-end AI software stack, including model development, optimization, deployment, and hardware acceleration technologies.
• Hands-on experience optimizing AI models for performance, power, and accuracy on hardware accelerators such as CPUs, GPUs, and NPUs.
• Strong understanding of modern machine learning architectures, including CNNs, RNNs, Transformers, and ensemble methods.
• Proficiency with AI frameworks and tooling such as PyTorch, TensorFlow, ONNX Runtime, and MLIR.
• Excellent written and verbal communication skills.
• Demonstrated ability to learn quickly, think critically, and adapt in a fast-paced and rapidly evolving technology environment.

Nice to have

• Experience using processor-specific optimization tools, libraries, and profiling and optimization tools to improve AI performance on CPUs, GPUs, and NPUs.
• Experience with PCIe or Windows MCDM/WDDM driver stacks.
• Prior experience with Qualcomm FastRPC and Windows MCDM drivers.
• Experience with transformer-based models such as BERT, GPT, T5, and Llama.
• Experience developing, optimizing, or deploying large language models (LLMs) or foundation models.
• Practical experience with developing middleware or system software, preferably for AI applications.

Details

• Location: Bangalore, India.
• Works closely with software and hardware architects, systems, hardware, architecture and test engineers, and other teams.