Embedded AI Software Engineer (C++17) for On-Device ML

Polluxa, Inc.; California (MO); On-site; USD 95,000 - 135,000; Full time

Job summary

Polluxa, Inc. is seeking a software engineer to develop a high-performance C++17 library for Qualcomm Hexagon Processors, focusing on embedded systems and real-time ML workloads.

You will design and optimize code, work with cross-compiler toolchains for Android, embedded Linux and QNX, and address issues across Qualcomm AI products. Join a globally distributed team, improve software quality processes, and contribute to model analysis tools and ML operations on device.

Qualifications

• 3+ years of relevant work experience in C++17 embedded software.
• Experience with modern C++ features and performance tuning.
• Background in mathematical algorithms and vector instructions.

Responsibilities

• Development of modern C++17 software library for Qualcomm Hexagon Processors
• Design and performance tune modern C++17 code for an embedded system
• Development of model analyzing tools for the internal and external customers
• Use cross compiler toolchains for embedded systems such as Android, embedded Linux and QNX
• Address issues found in existing and past Qualcomm AI products
• Implement and optimize modern C++17 machine learning operations on Hexagon Processors
• Debug customer machine learning use cases executing on Qualcomm AI Stack
• Communication across globally diverse team
• Participate in software quality process improvements

Skills

C++17

Multithreading

Embedded systems

Software performance optimization

Linux

Git

Docker

TensorFlow/PyTorch/ONNX

Cross-compiler toolchains

Education

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

Tools

Hexagon DSP SDK

Android cross compiler toolchains

embedded Linux

QNX

Job description

Polluxa, Inc. is seeking a software engineer to develop a high-performance C++17 library for Qualcomm Hexagon Processors, focusing on embedded systems and real-time ML workloads.

You will design and optimize code, work with cross-compiler toolchains for Android, embedded Linux and QNX, and address issues across Qualcomm AI products. Join a globally distributed team, improve software quality processes, and contribute to model analysis tools and ML operations on device.