Machine Learning Systems Engineer

Originally posted 30 June 2026 by the employer.

About the role

This role involves developing sensor-based solutions spanning early R&D to commercial deployment within the QCT sensors group. You will focus on AI and signal processing sensor architectures embedded across smartphones, automotive, IoT, smartwatches, and consumer electronics.

What you'll do

- Develop algorithms for single and multi-sensor fusion using digital signal processing (DSP) and ML/AI techniques. - Prototype and develop flows using high-level languages including MATLAB and Python. - Balance performance, power consumption, and computational complexity. - Produce reports on algorithm evaluation, validation, and benchmarking alongside complete design and user documentation. - Implement software in C/C++ on Qualcomm platforms while collaborating with global development and test teams.

What you'll need

- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 2+ years of Systems Engineering or related work experience; or a Master's degree with 1+ year of experience; or a PhD. - Experience with systems engineering activities across product life cycles.

Nice to have

- Bachelor's, Master's, or PhD in Electrical or Computer Engineering, or related area. - Experience applying digital signal processing, linear algebra, probability, statistics, and machine learning concepts such as supervised learning, unsupervised learning, feature extraction, classification, and regression. - Knowledge of inertial sensors or algorithm design using IMUs. - Publications in the field of signal processing or AI. - Hands-on experience with algorithm implementation and debugging.

Skills: sensor fusion, DSP, ML/AI techniques, inertial sensors, algorithm implementation