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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.
Additional Information
In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.
All documents must be submitted in PDF format and under 30MB in size.
If you experience issues uploading your resume, please send it along with the job posting URL to recruit@42dot.ai.
We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.
Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).
42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement
42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.
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