Gatik AI-posted about 22 hours ago
$200,000 - $260,000/Yr
Full-time • Mid Level
Onsite • Mountain View, CA
101-250 employees

We are seeking a Staff Software Engineer with deep expertise in localization for autonomous systems, especially in Lidar Odometry and Pose Graph Optimization. You will play a critical role in designing, implementing, and optimizing high-performance, real-time localization algorithms that enable robust and accurate navigation of autonomous vehicles. This position is ideal for someone who thrives in solving complex algorithmic and system-level problems and has a proven track record with C++ in large-scale production environments. This role is onsite 5 days per week at our Mountain View, CA office.

  • Design and develop high-performance localization modules using Lidar-based odometry and pose graph optimization techniques.
  • Architect robust and scalable systems for real-time state estimation on autonomous platforms.
  • Contribute to the full software lifecycle: design, implementation, testing, deployment, and maintenance.
  • Collaborate closely with mapping, perception, and Control teams to integrate localization into the broader autonomy stack.
  • Drive algorithmic innovation in SLAM, loop closure detection, outlier rejection, and sensor fusion.
  • Optimize code for efficiency, robustness, and real-time performance on embedded and edge compute systems.
  • Provide technical leadership, mentorship, and code reviews to elevate the team's overall engineering quality.
  • Stay current with the latest research in the localization and SLAM domain and evaluate opportunities to apply new techniques.
  • Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field.
  • 6+ years of total experience and 3+ years of hands-on experience working with Lidar Odometry and Pose Graph Optimization in real-world applications.
  • Expert proficiency in modern C++ (C++14/17/20) and strong software engineering fundamentals (design patterns, concurrency, memory management).
  • Strong understanding of SLAM, factor graphs, optimization frameworks (e.g., g2o, Ceres, GTSAM).
  • Experience with 3D point cloud processing, ICP, scan matching, and Lidar SLAM pipelines.
  • Familiarity with ROS/ROS2 and real-time robotics software development.
  • Experience working on autonomous vehicles, robotics platforms, or drone systems.
  • Knowledge of sensor fusion techniques combining IMU, GPS, Lidar, and camera.
  • Familiarity with Linux-based development, CI/CD pipelines, and performance profiling.
  • Publications or open-source contributions in the area of localization or SLAM.
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