Full-Stack Robotics Software Engineer

About the role

The position translates AI research into reliable, commercial-grade robotic performance across customer deployments.

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

Backend infrastructure and APIs are architected to support large-scale data collection, with monitoring, logging, and evaluation tools for real-time model performance verification by the AI team.

3D visualization tools are developed to process and display geometric data, rigid body transforms, and moving reference frames so researchers can interpret robot perception.

Cross-functional collaboration with AI, Controls, and Hardware teams accelerates the path from research hypotheses to deployed robotic capabilities in customer environments.

Requirements

The posting states a bachelor's degree requirement. The posting states a minimum of 2 years of experience.

5+ years of proven experience building highly reliable production software with an emphasis on Python and C++ for robotic systems.

A strong mathematical foundation in 3D geometry, rigid body transforms (SO(3)/SE(3)), and kinematics is required, with comfort using libraries such as NumPy, SciPy, or Pinocchio for motion planning.

Full-stack proficiency is required to build backend services and low-level software that interfaces with hardware SDKs or embedded systems in industrial settings.

Efficient system debugging across the network layer, device drivers, and geometric logic is necessary to isolate and resolve software-stack issues on real robots.

Ownership mindset is required, with hands-on testing on electromechanical systems and a bias for action to unblock high-priority delivery milestones.

A degree is required as stated in the official listing fields.

Years of experience between 5+ and 2+ are required across the full software stack and hardware interactions.

Practical notes

The role is based in Redwood City, CA, under full-time employment terms.

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

Roles that connect AI research to physical systems emphasize rigorous engineering and real-world reliability.

Teams building general-purpose robots use geometric reasoning, 3D data visualization, and large-scale data pipelines to validate model behavior.

Proficiency in Python and C++ remains common for stack-wide ownership in production robotic deployments.

Cross-functional coordination across AI, Controls, and Hardware is typical when moving research prototypes to fielded capabilities.

Engineers often use libraries for geometry and visualization to interpret and debug robot perception and control.

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.