Senior SLAM Engineer
Mountain View, United States
ENGINEERING – Autonomous Driving /
Full-time /
Hybrid
We are looking for the best
As a Senior SLAM Engineer at 42dot, you will lead the development of advanced localization and mapping technologies that form the foundation of autonomous driving. Leveraging cutting-edge geometric vision techniques, you will design robust SLAM pipelines that fuse data from multiple sensors to estimate the vehicle’s pose and reconstruct its surroundings in real-time. You will work closely with cross-functional teams across perception, planning, and robotics to ensure the seamless integration and deployment of SLAM systems in production-level autonomous vehicles.
Responsibilities
- Design and implement state-of-the-art SLAM algorithms for real-time localization and mapping using multi-modal sensor inputs (e.g., cameras, IMUs, GPS, wheel encoders).
- Develop robust online and offline state estimation methods for complex urban and highway environments.
- Focus on 3D geometric vision problems such as VSLAM, VIO, SfM, and scene reconstruction.
- Implement robust motion estimation, feature matching, loop closure, and map optimization pipelines.
- Apply non-linear optimization and filtering techniques (e.g., bundle adjustment, graph SLAM, EKF) to maximize system accuracy and robustness.
- Collaborate with sensor calibration and perception teams to improve system performance and consistency.
- Evaluate and benchmark system performance using large-scale datasets and real-world driving scenarios.
- Contribute to system integration, continuous validation, and deployment of SLAM modules on autonomous vehicle platforms.
- Mentor junior engineers and contribute to technical leadership within the team.
Qualifications
- PhD degree in computer vision, robotics, or a related field
- Minimum of 2 years of industrial or postdoctoral experience in SLAM, localization, or robotic perception
- Deep theoretical and practical understanding of SLAM systems, 3D geometry, and sensor fusion
- Hands-on experience with real-world datasets and deployment of SLAM pipelines in field environments
- Proficiency in modern C++ and Python, with strong software engineering practices
- Experience with optimization libraries (e.g., g2o, Ceres Solver) and robotics frameworks (e.g., ROS)
Preferred Qualifications
- Experience in large-scale autonomous driving or robotics system development
- Familiarity with sensor modeling and calibration for cameras, IMUs, GPS, and wheel encoders
- Expertise in real-time performance optimization, multi-threading, and hardware acceleration (GPU, SIMD)
- Contributions to open-source SLAM libraries or publications in top-tier conferences (e.g., ICRA, CVPR, RSS)Experience with mapping infrastructure, map maintenance, and life-long localization
- Strong communication skills and ability to collaborate across multidisciplinary teams
Interview Process
- Application Review - Coding Test - 1st Interview - 2nd Interview - Offer
- The process may vary by position and is subject to change.
- Schedule and results will be communicated via the email provided in your application.
Please refer to the videos from KCCV 2022 and UMOS Day 2021 for insights into 42dot Autonomous Driving, our autonomous driving AI software.
※ Please review the following information before applying.
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