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Commission Sensor Fusion Engineer Jobs (NOW HIRING)

OSI Engineering, Inc.

Lead Sensor Engineer

Palo Alto, CA · On-site

$300K - $400K/yr

Architect sensor-fusion strategies that combine multiple sensing streams into reliable inputs for the AI platform. * Partner closely with Electrical Engineering, Firmware Engineering, Product Design ...

JT4, LLC

Radar Fusion Engineer IV

Edwards, CA · On-site

$120K - $160K/yr

Radar Fusion Engineers must stay current with the latest advancements in radar technology and have ... Experience with Radar and Electronic Warfare principles, and sensor operations * Knowledge of Low ...

The Pennsylvania State University

$115K - $173K/yr

Design data fusion and estimation frameworks using heterogenous sensor network configurations ... Collaborate with computer vision algorithm developers and data scientists to integrate machine ...

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Commission Sensor Fusion Engineer information

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$10

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How much do commission sensor fusion engineer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for commission sensor fusion engineer in the United States is $49.97, according to ZipRecruiter salary data. Most workers in this role earn between $40.87 and $57.21 per hour, depending on experience, location, and employer.

What is the difference between Commission Sensor Fusion Engineer vs Calibration Engineer?

AspectCommission Sensor Fusion EngineerCalibration Engineer
Required CredentialsBachelor's or Master's in Electrical Engineering, Computer Science, or related fields; experience with sensor integrationBachelor's or Master's in Electrical Engineering, Mechanical Engineering, or related fields; expertise in calibration techniques
Work EnvironmentAutomotive, robotics, or aerospace industries focusing on sensor data integrationManufacturing, automotive, or aerospace sectors focusing on sensor accuracy and calibration
Industry UsageUsed in autonomous vehicles, drones, and robotics for sensor data fusionUsed in vehicle manufacturing, aerospace, and industrial equipment for sensor calibration

The Commission Sensor Fusion Engineer focuses on integrating and optimizing multiple sensor data streams for accurate perception systems, while the Calibration Engineer specializes in ensuring sensors are accurately calibrated for precise measurements. Both roles require technical expertise but differ in their primary focus within sensor systems.

How to become a commission sensor fusion engineer?

To become a sensor fusion engineer, typically a bachelor's degree in electrical engineering, computer science, or a related field is required, with many roles preferring a master's or higher. Gaining experience in signal processing, robotics, or autonomous systems, along with proficiency in programming languages like C++ or Python and familiarity with sensor technologies and data fusion algorithms, is essential. Certifications in related areas or hands-on experience with sensor integration and fusion tools can enhance job prospects.
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Commission Sensor Fusion Engineer jobs near you
Infographic showing various Commission Sensor Fusion Engineer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 83% Full Time, 10% Part Time, and 6% Contract. Highlights an 70% Physical, 1% Hybrid, and 29% Remote job distribution, with an average salary of $103,934 per year, or $50 per hour.

Machine Learning Systems Engineer -- Sensor Algorithms

Santa Clara, CA

Talentlab
See more jobs at Talentlabexternal

Full-time

Posted 19 days ago

Job description

Machine Learning Systems Engineer — Sensor Algorithms

Location: Santa Clara, CA
Focus: Multi-modal sensor fusion, signal processing, ML algorithms

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.

This is an R&D-oriented role developing algorithms for single and multi-sensor systems used in smartphones, wearables, IoT and other consumer devices. The work sits at the intersection of sensor fusion, signal processing, estimation and machine learning, with responsibility spanning algorithm design, evaluation and eventual deployment onto embedded platforms.

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.

What we're looking for

  • 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
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.