Join the growing team at Qualcomm focused on advancing state-of-the-art in

Machine Learning. The team uses Qualcomm chips extensive heterogeneous

computing capabilities to allow inference of trained neural networks on-device

without a need for connection to the cloud. Our inference engine is designed to help

developers run neural network models trained in a variety of frameworks on

Snapdragon platforms at blazing speeds while still sipping the smallest amount of

power. See your work directly impact billions of devices around the world.

Responsibilities: In this position, you will be responsible for the development and

commercialization of ML solutions like Snapdragon Neural Processing Engine

(SNPE) SDK on Qualcomm SoCs. You would be enabling AI/ML stack on various

platforms and optimize the performance on multiple hardware accelerators (like

CPU/GPU/NPU). You will have expert knowledge in deployment aspects of large

software C/C++ dependency stacks using best practices. You will also have to keep

up with the fast-paced development happening in the industry and academia to

continuously enhance our solution from software engineering as well as machine





learning standpoint.

Requirements:

- Masters or Bachelor’s degree in computer science or equivalent.
- 3+ years of relevant work experience in software development.
- Experience with embedded software development or equivalent.
- Basics of Deep-learning and familiarity with neural network operators.
- Experience with optimizing algorithms for hardware accelerators and parallel

architectures (like CPU/GPU/NPU).

- Strong development skills in C and C++.
- Excellent analytical and debugging skills.
- Valuable communication skills (verbal, presentation, written).

Preferred Qualifications

- Knowledge of processor architecture and system design fundamentals.
- Knowledge of object-oriented software development.
- Background in mathematical operations: linear algebra, fast-math libraries.
- Floating-point, Fixed-point representations and Quantization concepts.
- Knowledge of parallel computations, resource allocations in parallel computing

systems and associated languages like OpenCL, CUDA, etc. is a plus.

📌 Engineer II - SW DEV (Hyderabad)
🏢 FTProtech
📍 Hyderabad