SLAM Engineer
Job description
About the role
The team develops personal robots for home use, focusing on generalized robots that reclaim time by handling repetitive tasks. This role advances embodied AI and indoor navigation for a consumer hardware product. As an early member, you enable safe, natural home robot motion while shaping technology and product.
Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.
Key facts
What you'll do
LiDAR, camera, IMU, and odometry data are fused to build robust indoor SLAM so the robot can navigate complex home spaces. The robot estimates its pose and maps surroundings without drift, enabling reliable and safe motion in unstructured environments.
Multi-sensor calibration pipelines are developed so the robot's sensor suite delivers consistent, accurate data over time. Aligned measurements from cameras, LiDAR, IMU, and wheel odometry support perception and planning across the robot stack.
Perception and motion planning engineers define navigation and collision avoidance behaviors so the robot operates safely in dynamic home settings. Safe, smooth, and natural motions are generated as the robot interacts with people and objects in the home.
Requirements
The posting states a bachelor's degree requirement. Experience with vision-only or LiDAR-based SLAM pipelines allows the robot to estimate its pose and map surroundings reliably. Deep understanding of spatial math, including 3D rotation representations, frame transformations, and camera projections, keeps geometry consistent across sensors. Familiarity with multi-sensor time-synchronization methods ensures events are aligned precisely for reliable perception. Experience writing production-quality software in Python or C++ supports performance, safety, and long-term maintainability.
Nice to have
Production-grade SLAM experience in autonomous driving, AR/VR, or robotics helps the system scale to real homes and changing conditions. Familiarity with GTSAM enables efficient reasoning over spatial relationships and uncertainty. Experience with motion-capture systems supports precise evaluation and debugging of robot motion.
Practical notes
This role operates within a small, cross-functional team building the full robotics stack from sensors to user-facing value. The position may involve travel or occasional onsite presence as product and engineering workflows require. Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
Work in this field centers on perception, motion planning, and control for real-world robots. Common tools include SLAM frameworks, sensor drivers, and spatial math libraries. Success depends on robust software, careful calibration, and close collaboration across engineering functions.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.