Senior Autonomy Engineer

Brain Corp•San Diego, CA

1d•$179,505 - $224,381

About The Position

As a Senior Autonomy Engineer on Brain Corp’s R&D team, you will help define the next generation of software that enables robots to perceive, learn, and act in unstructured indoor environments. You will work across the autonomy stack, including learned perception and prediction, mapping, and motion planning, and deliver capabilities that generalize across the company’s robotic fleet. The role combines research literacy, production C++ and Python development, and hands-on debugging on robots in the lab. You will also help set technical direction, improve engineering quality, and mentor team members. Brain Corp is a San Diego-based AI company developing core technology for robotics. Its BrainOS® Robotics Platform powers a large global fleet of autonomous mobile robots used in commercial public spaces, including applications in floor cleaning and inventory management. The company reports powering more than 50,000 robots and is funded by SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Requirements

Master’s degree or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field, or equivalent demonstrated experience.
At least 5 years of relevant industry or research experience building autonomy, perception, or machine-learning systems.
Strong fluency in Python and C++ in a Linux environment.
Demonstrated track record of taking research ideas and papers into deployed implementations.
Depth in one or more of machine learning (supervised, self-supervised, imitation learning, or reinforcement learning), SLAM and state estimation, motion planning, or 3D perception.
Hands-on experience with PyTorch and/or JAX, modern training pipelines, and contemporary architectures such as transformers, diffusion models, and vision-language-action models.
Experience designing robotic systems with ROS 2 or comparable middleware and contemporary simulation tools such as Isaac Sim, MuJoCo, or Gazebo.
Comfort with the full machine-learning lifecycle, including data curation and labeling strategy, large-scale training, offline and online evaluation, and continuous deployment to production hardware.
Sound systems and software architecture judgment, including pragmatism about when learned approaches are preferable to classical approaches and vice versa.
Familiarity with modern engineering practices such as CI/CD, code review, observability, and iterative delivery methods such as Agile or Scrum.

Nice To Haves

Contributions to open-source robotics or machine-learning projects.
Publications at leading venues such as CoRL, RSS, ICRA, NeurIPS, CVPR, or ICML.
Experience with on-device acceleration, including TensorRT, ONNX, or custom CUDA kernels.

Responsibilities

Design, train, and deploy machine-learning systems for perception, SLAM, prediction, and motion planning to support safe navigation around people and obstacles.
Build and improve learned components, including transformer-based perception, vision-language models for scene understanding, diffusion or imitation-learning policies, and neural or Gaussian-splatting approaches to mapping; integrate them with classical estimation and planning where appropriate.
Translate research papers, open-source releases, and conference talks into production-quality implementations on robots.
Develop data engines and evaluation infrastructure that turn fleet logs into training data, regression tests, and deployed improvements.
Own features end-to-end, from prototyping through simulation and on-robot validation to fleet rollout, and measure their real-world impact.
Improve perception, mapping, and planning runtime performance on embedded GPU or accelerator hardware, using quantization, distillation, or kernel work where warranted.
Contribute to internal frameworks, simulation tooling, and developer experience to improve team velocity.
Provide guidance and mentorship to engineers across robotics, machine learning, and supporting software systems.

Benefits

Discretionary annual target bonus.
Stock options.
401(k) plan with matching, no waiting period, and immediate vesting.
Medical plan options, including an HSA with employer contribution, plus dental, vision, life, and disability insurance.
Employee Assistance Program and legal/identity support plans.
Pet insurance.
Flexible Spending Accounts for medical and dependent care.
Flexible vacation, paid sick leave, paid time off for community volunteering, 10 paid company holidays, and a winter company shutdown.
Daily on-site lunch available in the San Diego office.
On-campus gym, pool, and tennis courts in the San Diego office.
Colleague activities, including monthly game nights, hikes, wellness challenges, and community events.
Internal continuous-learning events.
Opportunities to share personal interests and hobbies with the company.