SLAM Engineer, Calibration, Mapping & Localization

DoorDash, Inc

Confirmed live 2 days ago High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $168,000–$247,000 / yr
Posted: 71 days ago
Freshness: Confirmed live 2 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $209k

This role $208k

$156k most similar roles pay here $261k

This role pays less than 52% of similar roles. Most pay $170,000–$247,112 — the shaded band above. At the midpoint, this role pays about $208k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About DoorDash, Inc

DoorDash, Inc. is an American company operating online food ordering and food delivery. It trades under the symbol DASH. With a 56% market share, DoorDash is the largest food delivery platform in the United States.

DoorDash, Inc currently has 187 open roles on FindRole.

Listed pay typically runs $144,800–$212,950 across 166 roles with salary data.

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At a glance

TL;DR · SLAM Engineer, Calibration, Mapping & Localization

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As a SLAM Engineer, Calibration, Mapping & Localization on the DoorDash Labs team, you will help scale a fleet of autonomous delivery robots by advancing large-scale HD mapping and robust localization capabilities. You will be responsible for architecting and deploying production-grade SLAM systems, designing 3D registration pipelines for noisy environments, and developing state estimation systems to handle real-world urban challenges. The role requires collaborating with perception, hardware, and autonomy teams to integrate solutions. Essential technical skills include proficiency in C++ and Python, along with expertise in 3D geometry, spatial reasoning, LiDAR and vision-based 3D registration, large-scale non-linear optimization, and state estimation techniques like EKF/UKF or factor graphs. Experience with deep learning frameworks and multi-modal localization using lidar, camera, and radar sensors is also highly valued for this robotics-focused role.

Skills

C++ Python SLAM 3D Registration State Estimation EKF UKF Factor Graphs Non-linear Optimization Deep Learning LiDAR Radar Embedded Systems 3D Geometry

What you'll do

Architect and deploy production-grade SLAM systems for large-scale HD maps.
Design and implement robust 3D registration pipelines for noisy, real-world environments.
Develop state estimation systems to handle localization challenges in dynamic urban settings.
Improve the quality and coverage of high-definition mapping data.
Build reliable relative and absolute localization systems for autonomous robot fleets.
Own technical architecture and drive implementation for core navigation features.
Set the technical direction for large-scale localization and mapping capabilities.

What we're looking for

Bachelor’s, Master’s, or PhD in Computer Science, Robotics, or a related technical field.
4+ years of industry experience in AV, Robotics, embedded systems, or an equivalent field.
Proficiency in C++, Python, and other relevant programming languages.
Expertise in 3D geometry and spatial reasoning.
Experience with LiDAR- or vision-based 3D registration including ICP variants and loop closure.
Expertise in large-scale non-linear optimization and state estimation techniques like EKF/UKF and factor graphs.
Experience with modern deep learning algorithms and frameworks is preferred.
Experience with multi-modal localization using lidar, camera, and radar sensors is preferred.