42dot is a technology company pioneering frictionless transportation services. 42dot develops technologies and platforms integrating autonomous driving, connected vehicles, and smart city infrastructure. Backed by Space Capital.
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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
- Exposure to autonomous driving or robotics across multiple vehicle classes
More about this role
42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles.
We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.
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.
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...
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