Bachelor's or Master's degree in Computer Science, Robotics, EE, Mathematics, or related field
2-4 years of experience in sensor calibration, SLAM, mapping, localization, or multi-sensor fusion
Solid software engineering skills in C++ and/or Python
Working knowledge of estimation theory, including Kalman filters and optimization-based fusion
Demonstrated ability to solve complex technical problems independently
Responsibilities
Design and implement sensor calibration systems for various sensors
Build and maintain mapping pipelines, including versioning and drift detection
Develop and enhance localization algorithms, focusing on sensor fusion and SLAM
Define accuracy, latency, and reliability requirements for outputs
Create tooling to validate calibration and localization quality at scale
Diagnose and resolve calibration and localization failures from testing
Benefits
Founding team opportunity with significant influence on technology direction
Work on cutting-edge technology across multiple vehicle classes
Collaborative environment focused on innovation and problem-solving
Potential for career growth in a rapidly evolving field
Exposure to diverse aspects of autonomous vehicle technology
Full Job Description
About the Role
ML-first does not mean ML-only: every model this team ships depends on a vehicle that knows precisely where its sensors are, where it is in the world, and how confident it can be in both. This role owns that foundation, building the calibration, mapping, and localization stack that every perception and planning model is built on top of, across a multi-vehicle-class fleet spanning passenger vehicles, robotaxis, buses, and trucks.
Founding team Opportunity
Most autonomy programs set their calibration and localization architecture years ago and are now stuck maintaining it. This team is establishing its framework now, and an early hire will help shape:
Sensor calibration methodology and tooling, both online and offline
Mapping strategy, representation, and drift-detection pipelines
Localization architecture and the technical roadmap as the fleet scales
Responsibilities
Design and implement sensor calibration systems (camera, LiDAR, radar, IMU) for factory and in-field use
Build and maintain mapping pipelines, including map creation, versioning, and drift detection
Develop and improve localization algorithms, including sensor fusion, odometry, and SLAM
Define accuracy, latency, and reliability requirements for outputs consumed by downstream teams
Build tooling to validate calibration and localization quality at fleet scale
Diagnose and resolve calibration and localization failures from on-road and simulation testing
Qualifications
A demonstrated ability to work through difficult technical problems methodically, with growing independence
Bachelor's or Master's degree in Computer Science, Robotics, EE, Mathematics, or related field
2-4 years of experience in sensor calibration, SLAM, mapping, localization, or multi-sensor fusion
Working knowledge of estimation theory, including Kalman filters, factor graphs, or optimization-based fusion
Solid software engineering skills in C++ and/or Python, with experience contributing to production-grade robotics systems
Preferred Qualifications
Exposure to autonomous driving or robotics across multiple vehicle classes
Exposure to HD map creation and maintenance pipelines
Experience with LiDAR, camera, or radar extrinsic calibration
Familiarity with functional safety requirements such as ISO 26262
The screening procedures may vary depending on the position, schedule, or other circumstances. You will be individually notified of the screening schedule and results via the email address provided in your application.
Compensation
$150,000 - $205,000
Additional Information
In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.
All documents must be submitted in PDF format and under 30MB in size.
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We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.
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