Controls Engineer

Humble Robotics; San Francisco (CA); On-site; USD 100,000 - 150,000; Full time

Job summary

A technology company specializing in autonomous vehicles seeks a Controls Engineer in San Francisco. You will design and optimize trajectory control systems for autonomous trucks, ensuring reliable execution of complex maneuvers. The ideal candidate has a degree in engineering or related field, experience with control systems, and proficiency in Rust and C++. This role offers the opportunity to work on groundbreaking technology within a close-knit team focused on innovation.

Qualifications

• Strong foundation in classical control theory: PID, LQR, state‑space methods.
• Industry experience developing real‑time control systems on hardware.
• Experience with estimation techniques and debugging controllers.

Responsibilities

• Design, implement, and deploy real‑time controllers for autonomous trucks.
• Develop vehicle dynamics models and perform system identification.
• Collaborate with ML and hardware teams on system integration.

Skills

Control theory

Rust

C++

ROS

Debugging

Education

BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics

Tools

Kalman filters

Bazel

Job description

About Humble Robotics

Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We’re building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today’s global logistics network.

We’re a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don’t believe culture can be engineered – but when it falls into place, it’s a once-in-a-lifetime adventure.

Progress has never felt so present.

Position Overview

We’re looking for a Controls Engineer to design and optimize trajectory generation and control systems for an autonomous truck. You’ll own safety-critical systems and ensure reliable execution of complex maneuvers, working closely with the ML team to integrate real-time path outputs while enforcing system constraints and safety checks. This role spans embedded systems and diverse compute platforms, and offers a rare opportunity to connect cutting‑edge ML with production autonomy on a small, high‑ownership team.

Key Responsibilities

• Design, implement, tune, and deploy real‑time controllers for autonomous trucks, taking ownership from modeling through on‑vehicle validation
• Develop and maintain vehicle dynamics models and perform system identification to support controller design and simulation fidelity
• Build and improve estimation and sensor fusion pipelines for vehicle state (Kalman filters, EKF/UKF, etc.)
• Validate controllers through SIL/HIL testing, closed‑loop simulation, and structured on‑vehicle experiments
• Debug, analyze, and iterate on controllers in the field using vehicle logs and telemetry
• Collaborate with teams across ML autonomy, system software, hardware, and safety on interfaces, requirements, and integration
• Contribute to the controls codebase in Rust with a focus on safety, reliability, real‑time performance, and maintainability
• Document design decisions, experiments, and tuning methodology clearly for the broader team

Minimum Qualifications

• BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent industry experience
• Strong foundation in classical control theory: PID, LQR, state‑space methods
• Industry experience developing real‑time control systems deployed on physical hardware
• Strong proficiency in Rust and/or C++ for performance‑critical systems
• Experience with estimation techniques (Kalman filters, complementary filters, or similar)
• Demonstrated ability to debug and tune controllers on real hardware
• Experience with ROS/ROS2/Autoware/Iceoryx or comparable robotics middleware
• Strong written and verbal technical communication
• Eligible to work in the United States

Preferred Qualifications

• Background in nonlinear, robust, or adaptive control
• Experience with Model Predictive Control (MPC) and optimization tooling (QP solvers, CasADi, Acado, etc.)
• Experience with Bazel or similar build systems for complex codebases
• Working knowledge of vehicle dynamics like tire models, lateral/longitudinal dynamics, and load transfer
• Comfort operating as an early team member—high ownership, low ego, fast iteration

Compensation

This role is eligible for base salary + benefits + equity compensation. Salary ranges are determined by role, level, and location. Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.

Equal Opportunity

Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances.