Sr. SLAM Engineer

About Lucid

At Lucid, we are creating exceptional mobility experiences through innovation to drive the world forward. Built on Lucid’s proprietary technology and software-defined vehicle architecture, our award-winning vehicles bring our “Compromise Nothing™” approach to the global automotive market. That means refusing to choose between performance and sustainability, design and engineering, ambition and integrity. In Lucid Air and Lucid Gravity, we have designed and built vehicles that have redefined their segments, combining exceptional range, performance, design, and expansive space in a single experience. 

We achieve this through deep vertical integration, with design, engineering, and production happening in-house across our global offices and manufacturing facilities. Our teams come from industries around the world, united by a shared commitment to excellence. By refusing to settle, you can help redefine what’s possible and shape the future of mobility.

The GeoAI team is seeking a Senior SLAM Engineer to build fleet-scale mapping and localization technologies that power next-generation navigation, ADAS, and autonomous driving systems. This role focuses on robust SLAM, multi-route mapping, localization, sensor fusion, and map maintenance using fleet-collected camera, LiDAR, GNSS, IMU, and vehicle telemetry data. 

You will play a key role in transforming large-scale fleet data into continuously improving localization maps, road graphs, and high-definition map assets used across GeoAI, Navigation, and ADAS products. 

Role:

SLAM and Localization:

• Design and develop visual SLAM, LiDAR SLAM, visual-inertial odometry (VIO), multi-sensor localization, multi-session SLAM, and multi-route SLAM systems. 
• Develop robust localization solutions using cameras, LiDAR, GNSS/RTK, IMU, vehicle odometry, and HD maps. 
• Build loop-closure, relocalization, place-recognition, and drift-correction capabilities for long-term localization performance. 
• Improve localization accuracy and availability in urban canyons, tunnels, parking structures, construction zones, and GNSS-denied environments. 

Fleet-Scale Multi-Route SLAM 

• Develop algorithms that jointly optimize trajectories and observations collected across repeated routes, multiple vehicles, and large geographic areas. 
• Build scalable pose graph and bundle adjustment systems for globally consistent maps. 
• Design place-recognition and loop-closure systems that match observations across different vehicles, lighting, seasons, weather, and roadway changes. 
• Develop multi-session map fusion and collaborative mapping solutions that combine repeated drives into a unified spatial representation. 
• Improve localization repeatability through long-term landmark management, route alignment, and historical fleet observations. 

Map Generation & Continuous Maintenance 

• Build scalable pipelines for localization map generation, HD map generation, lane-level mapping, road graph creation, and map quality validation. 
• Develop map change detection, incremental update, versioning, and rollback capabilities for continuously evolving road environments. 
• Create automated processes for landmark lifecycle management, fleet data aggregation, map freshness monitoring, and conflicting-observation resolution. 
• Build systems that safely incorporate qualified fleet observations into production map layers while preserving traceability and map consistency. 
• Define validation gates and quality metrics for map accuracy, coverage, freshness, reliability, and localization performance. 

Sensor Fusion & Calibration 

• Develop camera-LiDAR-GNSS-IMU fusion frameworks for localization, trajectory estimation, and map building. 
• Improve temporal synchronization, coordinate-frame management, calibration robustness, and calibration monitoring at fleet scale. 
• Develop localization confidence, integrity, and uncertainty metrics suitable for production ADAS applications. 
• Support sensor integration and localization performance across multiple vehicle platforms and hardware configurations. 

Production Deployment 

• Optimize SLAM, localization, and map optimization algorithms for large-scale cloud processing and vehicle deployment. 
• Build reliable distributed pipelines for processing large camera, LiDAR, GNSS, IMU, and vehicle-motion datasets. 
• Develop benchmarking, regression testing, visualization, debugging, and map QA tools. 
• Collaborate with Navigation, Perception, Vehicle Integration, Data Platform, and GeoAI teams to deliver production-ready mapping and localization systems. 

Qualifications:

• MS or PhD in Robotics, Computer Science, Electrical Engineering, Computer Vision, or a related field. 
• 5+ years of experience in SLAM, localization, mapping, robotics, or autonomous systems. 
• Strong software engineering skills in C++ and Python. 
• Deep understanding of visual SLAM, LiDAR SLAM, VIO, state estimation, sensor fusion, factor graphs, bundle adjustment, pose graph optimization, loop closure, place recognition, and multi-view geometry. 
• Hands-on experience with relevant libraries and frameworks such as GTSAM, Ceres Solver, OpenCV, Eigen, and ROS/ROS2. 
• Experience profiling, debugging, validating, and deploying complex robotics algorithms in production-oriented environments. 

Qualifications: 

• Experience building fleet-scale mapping and localization systems for autonomous driving, robotics, mobile mapping, or geospatial applications. 
• Experience with multi-session SLAM, multi-route SLAM, collaborative mapping, global pose graph optimization, and large-scale bundle adjustment. 
• Experience with HD maps, localization maps, map change detection, map updates, map versioning, and long-term landmark management. 
• Experience processing large-scale camera, LiDAR, GNSS, IMU, and vehicle telemetry datasets using distributed infrastructure. 
• Experience with production localization integrity, map quality evaluation, calibration monitoring, and system-level performance analysis. 
• Publications, patents, or significant technical contributions in SLAM, localization, robotics, computer vision, or mapping systems are a plus. 

What You'll Help Build 

Capability 

Impact 

Fleet-Scale Multi-Route SLAM 

Joint trajectory and map optimization across repeated drives and vehicles. 

Production Localization Stack 

Camera-LiDAR-GNSS-IMU localization for challenging road environments. 

Collaborative Map Fusion 

Unified maps built from multi-session, multi-vehicle observations. 

Map Generation Pipelines 

Localization maps, HD maps, lane geometry, road graphs, and landmarks. 

Continuous Map Maintenance 

Change detection, incremental updates, versioning, freshness, and validation. 

Mapping Quality Platform 

Accuracy, coverage, integrity, reliability, and regression monitoring. 

Ideal Candidate 

A hands-on SLAM engineer with deep expertise in localization, mapping, estimation, optimization, and sensor fusion. You are excited about solving large-scale geospatial challenges and building fleet-scale multi-route SLAM systems that continuously improve map quality and localization performance across an entire vehicle fleet. 

Compensation & Benefits: Lucid offers a comprehensive and competitive benefits package including medical, dental, and vision insurance; life and disability coverage; paid time off; paid holidays, paid sick leave; and a 401(k) retirement plan. Hourly/non-exempt employees accrue up to 120 hours paid time off, and salaried/exempt employee accrue up to 160 hours paid time off.  Eligible employees may also participate in Lucid’s equity program and/or a discretionary annual cash incentive program. Incentive and equity awards, if applicable, are determined based on individual performance, role scope, market considerations, and overall company results, in accordance with the terms of the applicable plans.  

Equal Opportunity: At Lucid, we believe diversity strengthens everything we build. Lucid Motors is proud to be an equal opportunity employer and is committed to providing an inclusive workplace for all. We consider all qualified applicants without regard to race, color, national or ethnic origin, age, religion, disability, sexual orientation, gender, gender identity or expression, marital status, or any other characteristic protected by applicable state or federal laws and regulations. 

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