Staff Software Engineer

About the role

This role advances Apptronik's humanoid robotics stack for Apollo, emphasizing real-world deployment, safety, and coordination across hardware and software teams.

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

Controls architecture evolves to serve the roadmap and adjacent teams, defining algorithms, real-time performance, testing, and long-term maintainability for the stack.

Whole-body control spans wheeled-base and biped platforms, coordinating base or leg motion with upper-body manipulation to broaden robotic capabilities.

Priority flexing targets the highest-impact problems, including learning-based hand control in simulation, mobile manipulation, teleoperation, and state estimation.

Robot performance envelope expands in speed, payload, reliability, and safety, delivering measurable and defensible improvements grounded in real-world data.

Cross-functional collaboration with hardware, systems, and reinforcement learning teams co-develops solutions and diagnoses system-level issues in production scenarios.

Requirements

Deep robotics fundamentals cover kinematics, dynamics, state estimation, and optimization or control theory relevant to real systems.

Whole-body control expertise includes WBC, OSC, QP-based control, or MPC for floating-base or mobile platforms demonstrated on physical hardware.

Hands-on experience with learning-based control or reinforcement learning in robotics, trained in simulation, validates controller behavior on real robots.

Breadth spans mobile manipulation, dexterous hand control, and teleoperation, moving between these domains to solve the hardest integration problems.

Production-grade software uses real-time C++ and Python for robotic systems, ensuring correctness, performance, and maintainability in deployed controllers.

Industry experience develops and validates controllers that run on physical robot hardware, with a track record of deployment at production scale.

Education or experience meets an MS or PhD in Robotics, CS, EE, ME, or a related field, or 8+ years of relevant industry experience in robot controls.

Physical requirements support prolonged desk work, lifting 15 pounds when needed, reading printed materials and screens, and effective hearing and speech.

Practical notes

This direct hire role is based in Austin, TX, operating under equal employment opportunity guidelines.

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 a human-centered robotics environment where safety, reliability, and real-world impact are central.

Use and extend a robotics stack that includes control, learning, simulation, and teleoperation tools.

Engage with cross-functional teams in a fast-paced setting that values measurable improvements and production readiness.

General knowledge of motion planning, estimation, and learning-based control methods is common across the field.

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.