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Sensor Fusion Algorithm Engineer information

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$106.4K

$173.5K

How much do sensor fusion algorithm engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for sensor fusion algorithm engineer in the United States is $106,386.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,000.00 and $132,500.00 per year, depending on experience, location, and employer.

What does a sensor fusion algorithm engineer do?

A Sensor Fusion Algorithm Engineer designs and develops algorithms that combine data from multiple sensors to create a more accurate or comprehensive understanding of an environment or system. This role is critical in fields such as autonomous vehicles, robotics, and IoT devices, where data from cameras, radars, lidars, and other sensors must be integrated for reliable perception and decision-making. These engineers apply knowledge of signal processing, machine learning, and statistical analysis to improve system performance and robustness. Their work enables smarter, safer, and more efficient technology solutions.

What are the key skills and qualifications needed to thrive as a sensor fusion algorithm engineer?

To excel as a Sensor Fusion Algorithm Engineer, you need a strong background in mathematics, statistics, signal processing, and computer science, typically supported by a relevant engineering degree. Proficiency in programming languages like C++, Python, and MATLAB, along with experience using simulation tools and machine learning frameworks, is crucial. Strong problem-solving abilities, teamwork, and effective communication skills distinguish top performers in this field. These skills and qualities are vital for developing robust algorithms that integrate diverse sensor data, enabling accurate perception and decision-making in advanced systems.

What are some common challenges sensor fusion algorithm engineers face when integrating data from multiple sensors?

Sensor Fusion Algorithm Engineers often encounter challenges such as handling sensor noise, dealing with differing data rates or latencies, and resolving conflicts between inconsistent sensor readings. Successfully integrating heterogeneous sensor data requires designing robust algorithms that can adapt to environmental changes and sensor failures. Collaboration with hardware engineers and software developers is also essential to ensure that sensor data is accurately synchronized and processed in real time.

What is the difference between Sensor Fusion Algorithm Engineer vs Robotics Software Engineer?

AspectSensor Fusion Algorithm EngineerRobotics Software Engineer
Required CredentialsBachelor's or Master's in Electrical Engineering, Computer Science, or related fields; experience with sensor data processingBachelor's or Master's in Robotics, Computer Science, or related fields; programming skills in C++, Python
Work EnvironmentEmbedded systems, sensor data integration, algorithm developmentRobot control systems, simulation, hardware-software integration
Industry UsageAutomotive, aerospace, consumer electronicsManufacturing, autonomous vehicles, service robots

The Sensor Fusion Algorithm Engineer focuses on developing algorithms to combine data from multiple sensors for accurate perception. In contrast, the Robotics Software Engineer designs and implements software for robot control and operation. While both roles require programming skills and knowledge of sensors, the Sensor Fusion Algorithm Engineer specializes in data processing algorithms, whereas the Robotics Software Engineer works on broader robot system integration.

What are popular job titles related to Sensor Fusion Algorithm Engineer jobs?

For Sensor Fusion Algorithm Engineer jobs, the most frequently searched job titles are:

Infographic showing various Sensor Fusion Algorithm Engineer job openings in the United States as of September 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $106,386 per year, or $51.1 per hour.

Sensor Algorithm Engineer - Hardware

Santa Clara, CA • On-site

Talentlab
See more jobs at Talentlabexternal

$143K - $189K/yr

Other

Posted 21 days ago

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:

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.

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