Machine Learning Engineer, 3D Vision&Localization

Why 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 self-driving at scale.
  
  
• Design and develop advanced SLAM systems to create, automate, and optimize large-scale 3D map-building pipelines for autonomous trucking environments.
  
  
• Implement robust, precise, and real-time onboard state estimation algorithms capable of maintaining accuracy and robustness under challenging conditions.
  
  
• Build and refine deep-learning-based observation models that enable resilient 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 operational 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, simultaneous localization and mapping (SLAM), or 3D vision theory and practice.
• In-depth knowledge and extensive experience in deep learning, computer vision, and modern transformer architectures.
• Demonstrated experience implementing SLAM/localization/3D vision systems in camera-based or LiDAR-based domains (or both) in real-world environments.
  
  
• 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, multi-disciplinary 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: large-scale map creation and updates, change detection, versioning, and map-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.