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Bonsai Robotics

Autonomy hardware and perception software

Senior Robotics Software Engineer - Simulation

Robotics & Autonomous SystemsUpdated on Nov 14
Full-timeSan Jose, CA, USA$180k - $215k /yr

About the Job

Requirements

  • Strong computer science fundamentals and systems fluency.
  • A Bachelor's, Master's, or PhD in Computer Science, Robotics, or a related field, with at least 5 years of industry experience in robotics software engineering and a significant focus on simulation.
  • At least 2 years of experience building software-in-the-loop, hardware-in-the-loop, or closed-loop evaluation systems used in production.
  • Strong proficiency in C/C++ and Python, and the ability to read and debug a large existing codebase.
  • Experience building simulation environments with platforms such as NVIDIA Isaac Sim, MuJoCo, Gazebo, or similar.
  • Familiarity with physics engines such as PhysX, Bullet, or MuJoCo.
  • Deep understanding of ROS 2.
  • Experience integrating simulation into CI/CD pipelines.
  • Strong debugging, testing, and problem-solving skills.

Responsibilities

  • Build and maintain simulation environments that model real field conditions, including orchards, vineyards, bedded crops, uneven terrain, and variable lighting and weather.
  • Own the interface between the simulator and the ROS 2 autonomy stack, and build software-in-the-loop and hardware-in-the-loop frameworks that run the full stack—including perception, planning, and controls—in closed loop.
  • Turn field logs into simulation by replaying recorded drives, reproducing field failures as regression scenarios, and growing a scenario library that covers machine edge cases.
  • Create and maintain sensor models for cameras, GNSS/RTK, IMUs, and LiDAR, including noise and failure modes, calibrated against real hardware.
  • Model vehicle dynamics and terrain interaction for multiple robot form factors, using system identification against real vehicle data.
  • Build automated scenario generation, evaluation metrics, and reporting so every autonomy-stack change is tested in simulation in CI before reaching a machine.
  • Keep simulation fast, deterministic, and reproducible, and measure how well simulation results predict real-world behavior.
  • Generate synthetic data for perception training, working with the machine-learning team on domain randomization and generative methods.
  • Work with the perception, controls, and platform teams to define simulation requirements and prioritize important sim-to-real gaps.

Desired Qualifications

  • Rust programming experience.
  • Exposure to agricultural, construction, or off-road robotics.
  • Experience with digital twins or synthetic data generation.
  • Experience using world models, such as NVIDIA Cosmos or similar generative video models, for synthetic data generation or scenario augmentation.
  • Experience with neural reconstruction, including 3D Gaussian Splatting, of scenes from real sensor data.
  • Familiarity with USD/OpenUSD scene formats.
  • Experience with sim-to-real transfer techniques, including domain randomization.
  • GPU-accelerated rendering or ray tracing for camera simulation.
  • Experience with NVIDIA Jetson or other embedded deployment.

About the Company

Bonsai Robotics

Autonomy hardware and perception software

Bonsai Robotics develops autonomy and automation solutions for vehicles used in harsh environments like orchards, vineyards, fields, and mines. Visionsteer uses a vision-based perception, planning, and controls stack to enable fast, reliable autonomous operation so novices can perform tasks with veteran-like proficiency. They provide autonomy-ready hardware kits and software for perception, planning, and controls that can be added to new machines or retrofitted to existing ones, and work without GPS or cellular connectivity. Their focus on GPS- and connectivity-independent autonomy for remote environments and close OEM/grower partnerships aims to deliver up to 60% ROI by improving operational efficiency and reducing downtime.

Company size
51-200
Company stage
Series A
Total funding
$25.5M
Headquarters
San Jose, CA
Founded
2022

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