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 cuttingedge geometric vision techniques you will design robust SLAM pipelines that fuse data from multiple sensors to estimate the vehicles pose and reconstruct its surroundings in realtime. You will work closely with crossfunctional teams across perception planning and robotics to ensure the seamless integration and deployment of SLAM systems in productionlevel autonomous vehicles.
Responsibilities
Design and implement stateoftheart SLAM algorithms for realtime localization and mapping using multimodal 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.
Apply nonlinear 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 largescale datasets and realworld 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
Handson experience with realworld 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 largescale autonomous driving or robotics system development
Familiarity with sensor modeling and calibration for cameras IMUs GPS and wheel encoders
Expertise in realtime performance optimization multithreading and hardware acceleration (GPU SIMD)
Contributions to opensource SLAM libraries or publications in toptier conferences (e.g. ICRA CVPR RSS)Experience with mapping infrastructure map maintenance and lifelong 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.
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