Job description

Sensor Algorithm Engineer – Hardware / ASIC Location: Santa Clara, California Focus: Sensor Fusion, DSP, Fixed-Point Algorithms, ASIC Implementation TalentLab is recruiting a Sensor Algorithm Engineer to develop advanced sensor fusion and signal processing algorithms targeted for hardware implementation . This is a systems and algorithm design role sitting between sensor algorithms and ASIC hardware . You'll develop and evaluate algorithms using MATLAB and Python, translate them into fixed-point designs suitable for hardware implementation, and work closely with hardware, systems and software engineers as designs move from early R&D toward commercial products. The technology is used across smartphones, wearables, IoT and other consumer devices, with a particular focus on extracting accurate information from inertial and other physical sensors. What You'll Work On • Develop single and multi-sensor fusion algorithms targeted for ASIC implementation. • Design and optimize fixed-point implementations of signal processing and sensor algorithms. • Prototype and evaluate algorithms using MATLAB and Python. • Work with accelerometer, gyroscope, magnetometer and other sensor data. • Apply DSP, estimation and statistical techniques to real-world sensor problems. • Balance algorithm accuracy against hardware constraints including performance, power and computational complexity. • Validate and benchmark algorithms throughout the development process. • Work closely with ASIC, systems, software, integration and validation teams. • Support C/C++ implementations where required for software-based development and validation. • Produce detailed algorithm design, evaluation and implementation documentation. What We're Looking For • Bachelor's, Master's or PhD in Electrical Engineering, Computer Engineering or a closely related discipline. • Strong foundation in digital signal processing and algorithm development . • Experience with fixed-point algorithm design and implementation. • Strong MATLAB and/or Python skills. • Experience with techniques such as Kalman filtering, adaptive filtering, linear algebra, probability and statistics. • Experience with sensor fusion, particularly using inertial sensors or IMUs. • Understanding of the considerations involved in translating algorithms from high-level models into hardware. • Hands-on algorithm implementation and debugging experience in software and/or hardware. Particularly Relevant Experience We're especially interested in candidates with experience in one or more of the following: • Fixed-point algorithm development. • DSP algorithms targeted for ASIC or FPGA implementation. • Hardware-oriented algorithm design. • Sensor fusion and estimation. • Kalman filters and adaptive filtering. • IMUs, accelerometers, gyroscopes and magnetometers. • MATLAB-based algorithm modelling and simulation. • Signal processing architecture and hardware/software partitioning. • C/C++ implementation of signal processing algorithms. • Machine learning techniques applied to sensor data. • Research or publications in signal processing, sensor fusion or related areas. The Role The key distinction in this position is the hardware destination of the algorithms . We're not looking for a general machine learning engineer or an embedded software developer. The strongest candidates will understand both the mathematics behind signal-processing and sensor-fusion algorithms and the practical constraints involved in implementing those algorithms efficiently in silicon. The role can accommodate candidates at different stages of their careers, including recent PhD graduates with directly relevant research in signal processing, sensor fusion, fixed-point design or hardware-oriented algorithm development. How to Apply? All qualified and interested applicants can apply directly to Gord Marriage by sending an email with attached resume to gord.marriage@talentlab.com. You may also apply directly on our website at www.talentlab.com. Although we thank all applicants for their interest, only those in consideration will be contacted.

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Must-haves

Sensor Algorithm Engineer – Hardware / ASIC
Location: Santa Clara, California
Focus: Sensor Fusion, DSP, Fixed-Point Algorithms, ASIC Implementation
TalentLab is recruiting a Sensor Algorithm Engineer to develop advanced sensor fusion and signal processing algorithms targeted for hardware implementation .
The technology is used across smartphones, wearables, IoT and other consumer devices, with a particular focus on extracting accurate information from inertial and other physical sensors.
What You'll Work On
Develop single and multi-sensor fusion algorithms targeted for ASIC implementation.
Design and optimize fixed-point implementations of signal processing and sensor algorithms.
Prototype and evaluate algorithms using MATLAB and Python.
Work with accelerometer, gyroscope, magnetometer and other sensor data.
Apply DSP, estimation and statistical techniques to real-world sensor problems.
Balance algorithm accuracy against hardware constraints including performance, power and computational complexity.
Validate and benchmark algorithms throughout the development process.
Work closely with ASIC, systems, software, integration and validation teams.
Support C/C++ implementations where required for software-based development and validation.
Produce detailed algorithm design, evaluation and implementation documentation.
Bachelor's, Master's or PhD in Electrical Engineering, Computer Engineering or a closely related discipline.
Strong foundation in digital signal processing and algorithm development .
Experience with fixed-point algorithm design and implementation.
Strong MATLAB and/or Python skills.
Experience with techniques such as Kalman filtering, adaptive filtering, linear algebra, probability and statistics.
Experience with sensor fusion, particularly using inertial sensors or IMUs.
Understanding of the considerations involved in translating algorithms from high-level models into hardware.
Hands-on algorithm implementation and debugging experience in software and/or hardware.

Nice-to-haves

None flagged.

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pythonmachine learning

Platform: catsone
Effort: medium