Real-Time VIO & SLAM Perception Scientist

Amazon; San Francisco, Northern (CA, KY); Hybrid; USD 172,000 - 223,000; Full time

Job summary

Amazon is seeking an Applied Scientist to advance Visual Inertial Odometry and sensor fusion for intelligent robots. You will own the pipeline from algorithm design to embedded deployment, ensuring real-time perception on resource‑constrained hardware and integrating learned perception with geometric methods.

The role emphasizes hands‑on work with sensors and data, collaboration across hardware, controls, and navigation teams, and leading projects from prototyping to production deployment.

Qualifications

• 3+ years of building models for applications.
• PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience.
• Experience in patents or publications at top-tier conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.
• Hands‑on experience developing and deploying Visual Inertial Odometry or visual‑inertial SLAM systems.
• Strong understanding of multi‑sensor fusion (cameras, IMUs, odometry) and state estimation.
• Experience optimizing perception algorithms for embedded or resource‑constrained hardware.
• Hands‑on experience with real sensor data, calibration, and physical robot platforms.
• Familiarity with modern ML approaches to perception (learned feature extraction, depth prediction, end‑to‑end odometry).

Responsibilities

• Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout.
• Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking.
• Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU‑accelerated edge devices) under strict latency and power constraints.
• Apply modern ML‑based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches.
• Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems.
• Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack.
• Lead technical projects from research prototyping through production deployment.

Skills

VIO

sensor fusion

C++

Python

state estimation

embedded hardware

ROS/ROS2

real sensor data

Education

PhD or Master's + 4+ years CS/CE/ML

Tools

NVIDIA Jetson

Qualcomm RB5

ROS/ROS2

Job description

Amazon is seeking an Applied Scientist to advance Visual Inertial Odometry and sensor fusion for intelligent robots. You will own the pipeline from algorithm design to embedded deployment, ensuring real-time perception on resource‑constrained hardware and integrating learned perception with geometric methods.

The role emphasizes hands‑on work with sensors and data, collaboration across hardware, controls, and navigation teams, and leading projects from prototyping to production deployment.