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Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain’s robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock thier abilties in orchestration with intelligent machinges.

As a Senior Autonomy Engineer on our R&D team, you’ll help define the next generation of software that lets robots perceive, learn, and act in unstructured indoor environments. You’ll work across the modern autonomy stack — from learned perception and prediction to mapping and motion planning — and ship capabilities that generalize across our fleet. We’re looking for someone equally comfortable reading a fresh arXiv paper, writing production C++/Python, and debugging behavior on a real robot in the lab. You’ll help set technical direction, raise the bar on engineering quality, and mentor others on the team.

• Design, train, and deploy machine learning systems for perception, SLAM, prediction, and motion planning that enable 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/Gaussian-splatting approaches to mapping — and integrate them with classical estimation and planning where it makes sense.
• Translate state-of-the-art research (papers, open-source releases, conference talks) into production-quality implementations on the robot.
• Develop data engines and evaluation infrastructure that turn fleet logs into training data, regression tests, and shipped improvements.
• Own features end-to-end: from prototype, through sim and on-robot validation, to fleet rollout, with measurement of real-world impact.
• Improve runtime performance of perception, mapping, and planning on embedded GPU/accelerator hardware (quantization, distillation, kernel work where warranted).
• Contribute to internal frameworks, simulation tooling, and developer experience that compound team velocity.
• Provide guidance and mentorship to engineers across robotics, ML, and the software systems that support them.

• Master’s Degree. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field — or equivalent demonstrated experience.
• 5+ years of relevant industry or research experience building autonomy, perception, or ML 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, RL), SLAM and state estimation, motion planning, or 3D perception.

• Hands-on experience with PyTorch (and/or JAX), modern training pipelines, and contemporary architectures (transformers, diffusion models, 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 ML lifecycle: data curation and labeling strategy, large-scale training, offline and online evaluation, and continuous deployment to production hardware.
• Solid systems and software architecture instincts; pragmatism about when a learned approach beats a classical one and vice versa.
• Familiarity with modern engineering practices: CI/CD, code review, observability, and iterative delivery (i.e. Agile, Scrum).
• Bonus: Contributions to open‑source robotics or ML projects, publications at top venues (CoRL, RSS, ICRA, NeurIPS, CVPR, ICML), or experience with on‑device acceleration (TensorRT, ONNX, custom CUDA kernels).

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential functions may require maintaining the physical condition necessary for sitting, walking or standing for periods of time; operating a computer and keyboard; talk and hear at normal room levels; using hands to finger, grasp, and feel; repetitive motion; close visual acuity to prepare and analyze data and figures; transcribing; viewing a computer terminal; extensive reading; lift, push, carry, or pull up to 20 pounds.

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

The anticipated salary range for candidates who will work in San Diego, California is $151,545 to $183,449. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi‑state employer and this salary range may not reflect positions that work in other states.