Edge AI Software Engineer: On-Device ML & Optimization

Polluxa, Inc.; San Diego (CA); On-site; USD 120,000 - 210,000; Full time

Job summary

Qualcomm AI Research is seeking talented AI software engineers to enable AI on edge devices. Join a multi-disciplinary team building GenAI solutions, optimizing models to run on edge hardware with mindful use of power, memory, and compute.

You will work on end-to-end embedded AI software, collaborate across hardware and software teams, and contribute to SDKs and tooling that accelerate customer deployment on automotive, mobile, and IoT devices.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• Experience with C/C++ and Python.
• Knowledge of DL and PyTorch.
• Strong software design and debugging skills.
• Android programming is a plus.
• Knowledge of neural network training/quantization is a plus.
• Familiarity with Qualcomm QNN SDK is a plus.

Responsibilities

• Development of end-to-end embedded AI software to train and finetune neural network models on Qualcomm leading edge hardware with optimal resources.
• Design and enhance the implementation of ML/AI SW stack, kernels, and runtime software to improve performance and power efficiency.
• Collaborating with our AI Processor Hardware team to implement high-quality solutions for new ML operators/layers that optimally utilize new capabilities in next-gen AI processors.
• Development of debugging/profiling tools and user-friendly SDKs for customers to foster rapid deployment of their new use cases.

Skills

C/C++

Python

Deep learning

PyTorch

Software design

Debugging

Android programming

Model training

Model quantization

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Tools

Qualcomm QNN SDK

Job description

Qualcomm AI Research is seeking talented AI software engineers to enable AI on edge devices. Join a multi-disciplinary team building GenAI solutions, optimizing models to run on edge hardware with mindful use of power, memory, and compute.

You will work on end-to-end embedded AI software, collaborate across hardware and software teams, and contribute to SDKs and tooling that accelerate customer deployment on automotive, mobile, and IoT devices.