SLAM Engineer, Calibration, Mapping, Localization

DoorDash

SLAM Engineer developing advanced mapping and localization solutions at DoorDash. Collaborating across teams to enhance fleet autonomy using production-grade SLAM systems.

Posted 7/2/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $168,000 - $247,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and deploying production-grade SLAM systems, with a strong focus on 3D registration and state estimation techniques. Proficient in collaborating across teams to deliver integrated solutions in the fields of robotics and autonomous vehicles.

Highest-signal resume keywords

C/C++ ProgrammingPython Programming3D Geometry ExpertiseState Estimation TechniquesLiDAR-Based 3D Registration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

3D RegistrationState EstimationLarge-Scale Non-Linear OptimizationSpatial ReasoningDeep Learning Algorithms

Certifications & Qualifications

B.S. in Computer ScienceM.S. in RoboticsPhD in Related Technical Field

Industry Keywords

Autonomous VehiclesRoboticsEmbedded SystemsMulti-Modal LocalizationFeature-Based Registration

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Architect and deploy production-grade SLAM systems for large-scale HD maps.
Design and implement robust 3D registration pipelines for real-world, noisy, and large environments.
Develop robust state estimation systems for localization handling real-world challenges.
Partner cross-functionally with perception, hardware, and autonomy teams to deliver tightly integrated solutions.

Requirements

What you’ll need

B.S., M.S., or PhD. in Computer Science, Robotics or related technical field
4+ years of industry experience working within the AV, Robotics, embedded systems or equivalent industry.
Experience with C/C++ and Python.
Deep expertise in 3D geometry, spatial reasoning
LiDAR- and/or vision-based 3D registration (ICP variants, feature-based, global registration, loop closure)
Large-scale non-linear optimization
State estimation (EKF/UKF, factor graphs, smoothing and filtering techniques)
Nice to Have: Experience with modern deep learning algorithms and frameworks
Nice to Have: Experience with multi-modal localization (e.g. leveraging lidar, camera, and radar sensors to achieve robust localization).

Benefits

Comp & perks

401(k) plan with employer matching
16 weeks of paid parental leave
Wellness benefits
Commuter benefits match
Paid time off
Paid sick leave
Medical insurance
Dental insurance
Vision insurance
11 paid holidays
Disability insurance
Basic life insurance
Family-forming assistance
Mental health program