United States onlyWhy Join Us
At Bot Auto, you’ll work on cutting-edge autonomous technologies that redefine how self-driving vehicles perceive and navigate the world. You’ll collaborate with experts in AI, mapping, and robotics to shape the next generation of intelligent mapping systems.
You Will
Be part of a multidisciplinary team of research scientists and engineers using an AI-first approach to enable safe, scalable self-driving.
Design and develop advanced SLAM systems to create, automate, and optimize large-scale 3D mapping pipelines for autonomous trucking environments.
Implement robust, precise, and real-time state estimation algorithms capable of maintaining accuracy and reliability under challenging conditions.
Build and refine deep-learning-based observation models that enhance perception and localization performance across diverse and complex real-world scenarios.
Integrate and validate localization and mapping solutions across onboard and offline systems, ensuring scalability, efficiency, and long-term stability.
Collaborate cross-functionally with perception, planning, control, and systems teams to align mapping and localization outputs with broader autonomy goals.
Required Qualifications
Master’s or PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
Strong background in robotics and simultaneous localization and mapping (SLAM) theory and practice.
Demonstrated experience implementing SLAM or localization systems in camera-based and/or LiDAR-based domains in real-world environments.
Proven experience applying deep learning to localization or mapping problems (e.g., learned feature extraction, odometry, registration, or neural SLAM).
Solid software engineering skills in C++ and Python.
Experience with sensor fusion involving LiDAR, cameras, IMU, and GNSS/RTK.
Strong quantitative foundation in linear algebra, probability, statistics, estimation theory, and optimization.
Comfortable working in a fast-paced, multidisciplinary autonomy environment with a hands-on, problem-solving mindset.
Excellent communication skills and the ability to collaborate effectively across teams.
Preferred Qualifications
Publications in SLAM, computer vision, or robotics.
Experience in the autonomous vehicle industry, particularly with on-road or fleet-scale systems.
Experience building and operating mapping infrastructure—including large-scale map creation and updates, change detection, versioning, and map-to-vehicle alignment.
Experience developing localization systems for GNSS-challenged or dynamically changing environments.
Familiarity with cloud platforms and distributed data pipelines for large-scale autonomy data processing.
