Principal / Staff Robotics Perception Engineer

Simbe Robotics•San Francisco, CA

3d•$190,000 - $240,000

About The Position

Simbe is building the AI powered operating system for physical retail. Our autonomous robots and multimodal computer vision platform turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and customer focused product design to help retailers improve shelf availability, price and promo execution, inventory accuracy, and store team productivity. Simbe is looking for a Principal or Staff Robotics Perception Engineer to serve as a critical bridge between our Computer Vision and Robot Software teams. This role owns the path from perception models and sensor data to real robotic behavior in production environments. You will help Tally understand dynamic retail stores, improve autonomy, and translate Simbe's computer vision capabilities into more reliable navigation, localization, calibration, and customer facing intelligence. Why This Role Is High Impact You will work on real robots operating in complex, high variance environments, not only offline benchmarks. Your work will improve autonomy and customer value across one of the largest real world retail robotics deployments. You will connect AI research, production computer vision, robot software, edge inference, and field performance.

Requirements

7+ years of experience in robotic perception, computer vision, machine learning, autonomous systems, or related production robotics work.
Strong proficiency in Python and C++ in Linux based development environments.
Hands-on experience with ROS and/or ROS2, robot sensor pipelines, and deployed robotics systems.
Experience with PyTorch, TensorFlow, ONNX, TensorRT, CUDA, or similar model training and inference tools.
Demonstrated track record of adoption of LLM assisted and agentic programming techniques
Strong understanding of object detection, segmentation, depth estimation, sensor fusion, calibration, visual localization, or SLAM.
Experience deploying real time AI models on embedded systems, edge GPUs, robots, or other constrained hardware.
Strong debugging, benchmarking, and systems thinking skills, with the ability to connect low level technical issues to product and customer outcomes.
Ability to collaborate across Computer Vision, Robotics Software, Product, Customer Success, Field Operations, and executive stakeholders.

Nice To Haves

Experience with AMRs, autonomous vehicles, drones, warehouse robotics, industrial automation, or service robots.
Experience with stereo cameras, RGBD cameras, LiDAR, fisheye cameras, depth sensors, or multi camera calibration.
Knowledge of visual SLAM, visual odometry, map alignment, path planning, or localization in dynamic indoor environments.
Experience with NVIDIA Isaac Sim, Isaac ROS, Omniverse, Jetson/Orin, or GPU accelerated robotics pipelines.
Experience taking research prototypes into production robotics software.
Experience building tools that help teams evaluate, debug, and improve robot perception at fleet scale.

Responsibilities

Own production perception pipelines. Lead the design, evaluation, integration, and optimization of perception systems used by Tally robots, including object detection, semantic and instance segmentation, depth estimation, tracking, sensor fusion, visual localization, and camera calibration.
Bridge CV and robot autonomy. Partner with Computer Vision, Robotics Software, Product, and Field teams to integrate perception models into the robot codebase and improve navigation, localization, scene understanding, and system reliability.
Improve real time performance. Profile and optimize neural networks on current and next generation robot hardware using Python, C++, ONNX, TensorRT, CUDA, and embedded GPU workflows.
Advance robot perception R&D. Explore emerging techniques in visual SLAM, visual odometry, depth estimation, open vocabulary detection and segmentation, multimodal perception, and simulation to identify practical improvements for Simbe's platform.
Develop system benchmarks. Define and maintain benchmarks that connect model quality to robot outcomes, including latency, compute, uptime, navigation success, localization robustness, false positives, false negatives, and customer facing accuracy.
Debug field failures end to end. Use logs, robot data, imagery, maps, telemetry, and model outputs to diagnose perception and autonomy issues observed in production stores.
Shape technical direction. Provide technical leadership, code reviews, architecture guidance, and mentorship for engineers working at the intersection of AI and robotics.