Amazon
Sr. Applied Scientist, Sensors, Sensor Algorithms
$192K–$260K
Sunnyvale, CA · Senior · Full-time · Posted Oct 7, 2026
- Experience
- 3+ years building machine learning models for business application; PhD, or Master's degree and 6+ years of applied research experience. Preferred: 5+ years building machine learning models or developing algorithms for business application and 5+ years of applied research.
- Education
- PhD, or Master's degree and 6+ years of applied research experience.
About the job
Develops and ships sensor algorithms combining signal processing and machine learning for Amazon devices, translating research into optimized consumer features.
What you'll do
- Develop and optimize sensor algorithms and machine learning models for Amazon products and hardware platforms.
- Collaborate with scientists, engineers, and product managers to turn business needs into technical solutions.
- Analyze data, present findings to stakeholders, and contribute to research publications and mentoring.
What they ask for
- 3+ years of building machine learning models for business application experience.
- PhD, or Master's degree and 6+ years of applied research experience.
- Experience developing and implementing deep learning algorithms, particularly computer vision algorithms.
- Expertise in Kalman filtering (EKF/UKF) or other Bayesian estimation for sensor fusion; rigid-body dynamics and pose estimation; and shipping ML and signal processing algorithms on Edge/Embedded devices.
Nice to have
- 5+ years of building machine learning models or developing algorithms for business application experience; 5+ years of applied research experience.
- Experience with VIO / SLAM, MEMS IMU error modeling and calibration, factor-graph optimization or complementary filtering, sensor simulation, or shipping algorithms in high-volume consumer electronic devices.
Pay
192,200.00 - 260,000.00 USD annually (base salary)
Tools
machine learning, signal processing, deep learning, computer vision, Kalman filtering (EKF/UKF), Bayesian estimation, IMU, UWB
AI focus
Develops machine learning and sensor-fusion algorithms, including deep learning and computer vision, for device-based sensing and user experiences.
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