Machine Learning Systems Engineer - Sensor Algorithms

This is not a traditional ML software engineering or model deployment position. We’re particularly interested in engineers with strong research foundations in sensor algorithms, signal processing and statistical methods.

What you’ll work on

• Develop algorithms for single and multi-sensor fusion using ML/AI and statistical techniques.
• Prototype and evaluate algorithms using Python and MATLAB.
• Work with inertial sensors and IMU data, including accelerometers and gyroscopes.
• Design strategies for data collection, analysis, validation and benchmarking.
• Evaluate trade-offs between algorithm performance, computational complexity and power consumption.
• Translate algorithm designs toward embedded implementation in C/C++.
• Collaborate with systems, software, integration and test engineers throughout the product lifecycle.

• PhD or Master’s degree in Electrical Engineering, Computer Engineering or a closely related discipline.
• Strong background in signal processing, probability, statistics and estimation.
• Experience with sensor fusion and/or inertial sensing.
• Understanding of supervised and unsupervised learning, feature extraction, classification and regression.
• Strong Python and/or MATLAB skills.
• Hands-on algorithm development, experimentation and debugging experience.
• Research or publications in sensor fusion, signal processing, estimation or related areas are highly valued.

Recent PhD graduates with relevant research experience are strongly encouraged to apply

TalentLab is working with a leading semiconductor and edge-computing technology company on an opportunity for a Machine Learning Systems Engineer focused on advanced sensor algorithms.