Vetted Robotics Engineers

“Robotics/embedded platform engineer who led compute provisioning and ROS2 platform development for a smart electrical panel, building a full ROS2 stack that bridges mobile app requests (via AWS IoT/MQTT) to signal-level CAN commands and returns telemetry/logs to the cloud. Demonstrated strong full-stack debugging by resolving flaky CAN traffic down to a custom PCB transceiver standby-pin grounding issue, and improved real-time behavior by refactoring middleware into C++ with timer-scheduled publishes to meet firmware watchdog expectations.”

“Robotics software engineer with ROS2 multi-robot experience spanning decentralized signal source localization (LoRa RSSI on TurtleBot3) and a master’s-thesis project on collaborative object transportation with 4 robots. Strong in sim-to-real debugging—implemented noise modeling (RBF) and practical hardware/coordination fixes (CoG tuning, clock sync/flags) to make algorithms work reliably on real robots.”

“Robotics/embedded engineer with hands-on firmware ownership for closed-loop motor/vision systems and strong ROS1 navigation experience (move_base, gmapping, robot_localization), including EKF sensor fusion to eliminate localization drift to sub-10cm accuracy. Also brings IoT distributed pub/sub expertise (30+ devices over MQTT, 99% uptime) plus Unity AR/VR simulation and computer-vision test automation that saved 100+ hours.”

“Robotics software engineer with ~3 years of ROS experience spanning drone autonomy and perception. Recently improved drone barcode scanning by shifting to segmentation and deploying an optimized instance-seg model to edge hardware (FP16 quantization, convex-hull masks), while also building ROS drivers/parameters for field-tunable behavior. Has hands-on experience integrating LegoLOAM and calibration/TF systems, including creating RViz visualization tools to validate transforms and debugging real-world drift issues caused by lighting/glare.”

“Robotics software engineer who helped build a startup "robo-chef" system end-to-end, including pick-and-place simulation using ArUco-marked stations and smooth motion planning. Hands-on ROS 2 integrator across LiDAR/IMU/camera perception-to-navigation stacks (Nav2, SLAM Toolbox, ros2_control), with demonstrated ability to debug real-time timing drift and improve repeatable placement through calibration and motion blending. Uses Gazebo simulation plus Docker/CI pipelines to validate and deploy robotics software reliably.”

“Deployment engineer at a robotics startup who owned end-to-end field deployments in greenhouse environments, including integrating humanoid robots (XArm 6), tuning perception stacks for real-world lighting shifts, and coordinating rapid fixes with hardware/software teams. Experienced debugging complex robotics integrations (LiDAR + NVIDIA Jetson + ROS2 + networking) and hardening solutions by automating configuration at boot, while also working directly with customers and training operators for ongoing support.”

“Robotics/ML engineer who benchmarks and adapts open-source robot action models, building synthetic datasets in Isaac Sim and modifying vendor code to scale training across multiple GPUs. Also built a production-style computer vision pipeline at Zortag—training a tiny YOLO-based classifier for fake-vs-real label detection and deploying it in a real-time iOS app with additional display/spoof detection.”

“Robotics/ROS engineer who led development of ROS 2 nodes for supervising and making safety/mission decisions for autonomous fixed-wing UAVs using PX4 and Gazebo, including handling sensor/battery failures, wind, and obstacle conditions. Has hands-on experience debugging ROS2 multi-node communication (QoS, publish rates) and navigating sim-to-real deployment from SITL to real flight hardware.”

“Founding Robotics Research Engineer at Streamline Robotics building precision-agriculture automation: integrated FANUC + PLC harvesting with a Farm-ng Amiga (Jetson) platform using ROS2 Visual SLAM for GPS-free greenhouse navigation. Developed real-time YOLOv8 tomato detection/ripeness estimation for selective harvest and configured Cognex D900 3D inspection, plus redesigned FarmBot Genesis XL and built an automated imaging/labeling pipeline for growth tracking and adaptive watering.”

“Robotics software engineer at Quant Robotics focused on perception for automated welding/assembly cells, working with LMI Co-Cutter 3D sensors and point-cloud registration. Previously implemented ROS 2 Humble navigation on a Clearpath Jackal by rewriting the NAV2 local controller with a constrained NMPC approach, optimizing for low-latency behavior via C++ and GPU offload. Hands-on with industrial ABB robots (IRB 6700/2600), multi-frame calibration, simulation in Gazebo/RViz, and Docker-based deployment/testing workflows.”