Simulation Engineer

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.

Open to a range of experience levels

We’re looking for a software engineer to join our simulation team. You’ll build the systems and tools that support closed-loop model testing, synthetic data generation, and sensor simulation. This work will work heavily with modern neural rendering approaches: Gaussian splatting, world models, and learned sensor models.

We’re a small team early in the build. You’ll have real influence over both what we build and how we build it.

Build and maintain Python pipelines and tooling for closed-loop testing and synthetic data generation

Integrate modern neural rendering techniques into our sensor simulation stack (e.g., Gaussian splatting, NeRFs, world models)

Expand and maintain the scenario library and benchmark suite used to evaluate perception, planning, and control

Develop synthetic data generation workflows, including scenario and agent behavior generation, to support model training

Work closely with ML and autonomy engineers to measure and reduce sim-to-real gaps, ensuring simulation reflects real-world behavior

BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent industry experience

Strong proficiency in Python (primary language of the simulation stack)

Experience working with simulation systems, ideally in robotics, autonomous vehicles, or other high-fidelity domains

Eligible to work in the United States

Experience with neural rendering or generative simulation (e.g., Gaussian splatting, NeRFs, world models, diffusion-based methods)

Depth in one or more areas of simulation: closed-loop testing, scenario design, log replay, or sensor simulation

Experience building benchmarks or evaluation frameworks used across a team

Experience developing synthetic data pipelines that improved downstream model performance

Familiarity with real-time robotic systems and their constraints on simulation fidelity

Comfortable working on a small team with high ownership and fast iteration cycles

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.

As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact legal@humblerobotics.ai to exercise this right or if you have further questions on the use of AI tools in our hiring process.

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.

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