Team Lead, Localization and Mapping Research

Job description

A WORLD EMPOWERED BY AUTONOMY. WE BUILD ROBOTIC VEHICLES TO IMPROVE LOGISTICS SAFETY, FORGE A GREENER EARTH, AND ENHANCE HUMAN LIVES. We are a closely-knit team aspiring to change the world through disruptive technology. We are innovators. We are tinkerers. We are problem-solvers. And we have a fair amount of magic dust up our sleeves. We have a plan for fleet-level deployment of autonomous vehicles, and we are looking for the best-of-the-best to join us in making this a reality. ABOUT VENTI TECHNOLOGIES Based in the U.S. and Asia, Venti Technologies is the leader in safe-speed autonomous logistics systems, developing the future of goods transportation. Using rigorous mathematics, deep learning, and theoretically-grounded algorithms, Venti has a proprietary collection of autonomy technologies including a suite of powerful logistics algorithms. Venti’s proven value proposition of saving costs, increasing vehicle utilization, and improving safety is recognized by customers and driving growth. Launched in 2018, Venti brings together an unsurpassed team internationally. The company has autonomous systems deployed in Asia for industrial and logistics sites and a growing pipeline. Venti has offices in Cambridge (Massachusetts, USA), Suzhou (China), and Singapore – our Asian headquarters. We are seeking a Team Lead, Localization and Mapping Research to guide a multi-disciplinary team of localization and mapping research scientists, software engineers, and mapping operations specialists. In this role, you will drive the research roadmap, essential tool developments, scalable map generation, scaling of simulation regression tests, and live autonomy stack core autonomy modules for safety critical applications to driverless trucks in complex logistics yards. Our autonomy solutions must overcome environmental challenges not limited to high vibration/shock (industrial vehicle platforms/loads), high environmental change (shipping container stock variance), high occlusions from large actors/structures, all weather 24hr everyday operational demands, and high precision alignments for parking or interfacing with specialized logistics equipment. This role combines technical leadership with system architecture ownership. You will stay abreast of current research trends and mentor the team to translate robotics algorithms into robust, real-world systems. You will work closely with perception, planning, controls, and testing/operations teams to deliver production-grade autonomy solutions for real-world deployments. Role responsibilities - Lead the design and development of localization and mapping systems for autonomous logistics vehicles - Architect scalable and automated HD map generation, maintenance, regression and deployment pipelines - Develop robust multi-sensor localization solutions using LiDAR, GNSS, IMU, cameras, and wheel odometry - Improve localization accuracy and reliability in GPS-denied or dynamic industrial environments with GPS interference. - Define software architecture, performance metrics, testing strategies, and deployment standards - Collaborate with perception, planning, systems, software infrastructure, and data software & services teams to integrate localization and maps into the autonomy stack - Mentor and grow a team of engineers and researchers, fostering a culture of innovation, ownership, and delivery. - Drive technical roadmap, project prioritization, and engineering execution - Support field testing, debugging, and deployment activities Required experience - Educational Background: Ph.D. or Master’s degree in Computer Science, Robotics, Engineering, or a related field, with a focus on localization and/or mapping for autonomous systems. - 7+ years of experience in robotics, autonomous vehicles, or localization/mapping systems - 2+ years of technical leadership or people management experience - Strong proficiency in C++, GPU programming, and experience with real-time robotic systems (preferably familiar with ROS/ROS2) - Deep understanding of: - SLAM algorithms - Sensor fusion including Lidar, Camera, GNSS-INS - State estimation including Kalman Filters - Lidar and visual odometry methods - HD mapping systems, including tool development and data pipelines - Machine learning approaches for localization and map features/semantics - Sensor calibration and degradations/maintenance in real outdoor robotics deployments - Safety critical software development processes including simulation regression testing and fleet-scale release validation - Leadership and Mentorship: Experience leading technical projects, mentoring engineers, and contributing to organizational growth. - Collaboration & Communication: Excellent communication skills for working across multidisciplinary teams and influencing technical direction.