Sensor Fusion & DSP Engineer — Embedded ML

Talentlab; Santa Clara (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

TalentLab in Santa Clara, CA, seeks a Sensor Systems Engineer focused on advanced sensing for smartphones, wearables, IoT and other embedded devices. This role centers on algorithm and systems engineering rather than traditional software development, combining DSP, sensor fusion, estimation and machine learning to develop next-generation sensing capabilities.

You'll design and implement single and multi-sensor fusion algorithms, work with IMU data, apply Kalman and adaptive filters, prototype in

Qualifications

• Strong background in digital signal processing and estimation techniques.
• Experience with IMU or other physical sensor data.
• Exposure to machine learning techniques including classification, regression and feature extraction.

Responsibilities

• Design and develop single and multi-sensor fusion algorithms using DSP and ML techniques.
• Work with accelerometer, gyroscope, magnetometer and other sensor data.
• Apply Kalman filtering, adaptive filtering, linear algebra, probability and statistics.
• Prototype algorithms using MATLAB and Python.
• Evaluate and benchmark algorithms across accuracy, performance, power and computational complexity.
• Support implementation of algorithms in C/C++ on embedded platforms.
• Collaborate across R&D, systems engineering, software integration, validation and deployment.

Skills

DSP

Estimation techniques

Sensor fusion

Machine learning

Education

Bachelor's/Master's/PhD in Electrical Engineering or Computer Engineering

Tools

MATLAB

Python

C/C++

Job description

TalentLab in Santa Clara, CA, seeks a Sensor Systems Engineer focused on advanced sensing for smartphones, wearables, IoT and other embedded devices. This role centers on algorithm and systems engineering rather than traditional software development, combining DSP, sensor fusion, estimation and machine learning to develop next-generation sensing capabilities.

You'll design and implement single and multi-sensor fusion algorithms, work with IMU data, apply Kalman and adaptive filters, prototype in