Vetted Robot Operating System (ROS) Professionals

“System-level robotics software engineer with production experience in both ROS 1 and ROS 2 who served as technical owner for an initial ROS1→ROS2 migration, including catkin→ament/colcon and refactoring core communication nodes. Strong in hardware-validated integration work—debugged intermittent message drops by tuning ROS 2 QoS for embedded firmware interfaces and stabilized real-time navigation behavior through timing/telemetry analysis and cross-team coordination.”

“University Rover Competition autonomous-systems lead who architects and debugs a full ROS 2 autonomy stack (Nav2, vSLAM, EKF fusion) and backs it with strong engineering hygiene (Docker + GitHub Actions CI running headless Gazebo and colcon tests). Also has industry-facing ROS 2 hardware integration experience, building a ros2_control plugin for a Unitree G1 arm using CycloneDDS and optimizing real-time behavior via QoS tuning.”

“Robotics software engineer with hands-on ROS 2 experience across drones, mobile robots, and manipulators. Built an end-to-end visual SLAM + navigation stack on a real robot using RTAB-Map, and implemented ROS 2-based coordination between a mobile robot and manipulator for camera-triggered object pickup. Optimizes real-time behavior by moving performance-critical code to C++ and deploying TensorRT-compressed models.”

“Robotics software engineer with deep ROS2 experience who built a modular autonomous robotics stack (perception/sensor fusion, localization+mapping, and planning). Led development of a LiDAR+camera fusion and multi-object tracking pipeline (PCL + YOLO + Kalman filtering) and debugged real-time SLAM/localization issues via QoS/timestamp synchronization, EKF tuning, and SLAM Toolbox parameter optimization using Gazebo/RViz and rosbag replay.”

“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”

“Robotics-focused full-stack engineer with hands-on ROS experience building sensor-processing and control nodes, plus a track record of debugging and optimizing real-time robot responsiveness via profiling and message-timing analysis. Uses Webots for pre-hardware validation and Docker/CI/CD to standardize deployments and catch issues early.”

“Robotics/embedded candidate who built an IoT smart shoe for visually impaired users, implementing real-time obstacle detection with ultrasonic sensors and haptic feedback on Arduino. Has practical ROS experience (RViz/Gazebo) and improved reliability in distributed systems by hardening an Arduino-to-ROS serial protocol with framing, strict parsing, and sensor-noise filtering; also containerized ROS environments with Docker for reproducible simulation and onboarding.”

“Robotics Software Engineer with 2.5 years at the Army Research Lab building production tools and cloud infrastructure for large-scale ROS/Unity simulation on AWS. Created a Python GUI to streamline analysis of massive (100GB) ROS bag/MCAP datasets and has deep ROS2/Nav2 performance debugging experience (executor/QoS/TF tracing). Also built an in-house ROS perception pipeline for an assembly-line use case, reaching 92% accuracy.”

“Robotics software engineer with hands-on depth across simulation (Isaac Sim, Gazebo, Webots), ROS/ROS2 integration, and real-time embedded control. Led an end-to-end quadruped (12-motor) Isaac Sim build from Fusion 360 CAD-to-URDF through physics tuning to achieve a stable walking gait, and optimized a 5-servo arm by cutting IK compute time by 60%+ using lookup tables to eliminate jitter.”

“Recent UC Riverside master’s graduate focused on uncertainty-aware imitation learning for indoor robot navigation, building a full ROS 2 Humble stack (perception, learned policy, uncertainty estimation) with adaptive speed control. Demonstrated strong real-time robotics debugging and systems skills, achieving 92% autonomous navigation success across 100 trials and improving reliability through uncertainty calibration and SLAM/loop-closure optimization.”

“Robotics software engineer at Earthwise building a full ROS2 Humble warehouse AMR stack for bin picking—owning perception (Livox/Orbbec/RPLidar fusion + calibration), Nav2 navigation with custom planners/behavior trees, and application-layer nodes (barcode scanning, safety monitoring, web HMI). Demonstrated strong real-world debugging and performance tuning (sub-cm AprilTag docking; ~80% reduction in localization failures) plus solid simulation/CI practices (Gazebo + Docker + GitHub Actions).”

“Robotics software/vision engineer with hands-on experience building motion-tracking systems that fuse camera-based 3D tracking with IMU orientation to reproduce tool motion for automated spray painting. Has implemented ROS nodes/packages for Orbbec camera streaming and SAM3-based segmentation, plus CAN bus coordination between robots and Dockerized deployment for a pick-and-place robotic cell.”

“Robotics software engineer (2 years) at a startup building a universal fleet management system, owning core integrations and real-time data pipelines for heterogeneous AMR/AGV fleets. Implemented Kalman-filter-based collision prediction integrating RTLS for human-driven forklifts, built MQTT microservices aligned with VDA5050, and is now architecting a PostGIS-backed path-planning service for dynamic, traffic-aware routing with future ML optimization.”

“Robotics software architect who built an automated pick-and-place palletizing prototype at BLACK-I-ROBOTICS, spanning perception (multi-RealSense fusion, segmentation, 6D pose, ICP), GPU-accelerated motion planning (MoveIt 2 + NVIDIA CuRobo), grasp generation, and safety (human detection + safe mode). Also brings cloud/CI/CD depth from VERIDIX AI (AWS Cognito/Lambda/ECS and CodePipeline stack) and demonstrated strong debugging chops by reducing outdoor rover EKF drift to ~5 cm via Allan variance-based IMU tuning.”

“Robotics/Perception Software Engineer at Berkshire Grey who built and hardened a production ROS-based perception + supervision stack for autonomous trailer-unloading robots (RGB-D + LiDAR), including grasp/geometry estimation and segmentation. Diagnosed real-time behavior issues by instrumenting ROS pipelines, then implemented runtime RANSAC-based compensation for LiDAR yaw bias and TF-window validation; also supports containerized deployment on Kubernetes and is actively porting the system from ROS1 to ROS2.”

“Robotics software engineer who built a full LiDAR SLAM pipeline from scratch in C++ (ICP, pose graph optimization, loop closures) and validated it quantitatively against ground-truth datasets. Extensive ROS2 experience from academics and an internship building a localization system, plus practical deployment work using Docker across x64 and ARM edge devices; also trained RL policies for TurtleBots in Gazebo.”

“Robotics software engineer with a Master’s in Robotics who built a digital twin of an excavator by creating a high-fidelity URDF (kinematics, joint limits, inertial properties) to stress-test controllers near saturation/limit conditions using ROS2 + MoveIt. Has hands-on ROS/ROS2 experience building perception (AprilTag/OpenCV) and sensor interface nodes (IMU/encoders/CAN), plus data-driven debugging and SLAM tuning for GPS-denied navigation using ROS bags and loop-closure validation.”

“Software engineer with robotics and ML background (BS Software Engineering w/ Robotics minor; MS CS w/ ML minor) who built autonomy-focused student robotics projects combining RFID + camera sensing, path planning (Dijkstra), and fuzzy logic, and experimented with neural-network approaches. Also brings production-grade software practices from a Dell software analyst role, emphasizing maintainability, documentation, and testing for real-time systems.”

“Robotics/AV perception engineer who built a semantic-segmentation road detection system and integrated it into a ROS-based real-time pipeline (ROS bag camera feed to live monitor) achieving ~12 FPS. Strong in practical deployment work: solved multi-library versioning issues (ROS/OpenCV/TensorFlow), containerized the stack with Docker, and optimized inference by shifting runtime to C++ for large latency gains on NVIDIA hardware.”

“Robotics software engineer with a Master’s thesis building an end-to-end monocular-vision pick-and-place controller for construction use cases on TurtleBot3 + OpenManipulator, spanning synthetic data creation, transfer learning, simulation in Gazebo, and real-robot deployment. Leveraged ROS distributed architecture to run two heavy AI models across networked GPUs to achieve usable real-time performance, and has production CI/CD experience as a Senior Software Engineer in AI/analytics.”

“Robotics/perception engineer who led and owned ARC, a cooperative perception system for autonomous vehicles that aligns and fuses multi-vehicle LiDAR point clouds in real time. Built a ROS-based multi-node pipeline with grid-based spatial reasoning and motion-compensated data sharing, achieving <20 ms compute latency and sub-7 cm alignment error; accepted to ACM SenSys 2026.”

“Robotics software engineer leading a GNSS localization effort that fuses GPS, wheel encoders, and camera data via a Kalman filter with robust sensor rejection. Has built ROS/ROS 2 packages (including GPS waypoint following and obstacle avoidance) and has field-tuned motion planning for an autonomous robot operating around penguins in Antarctica, plus handled Docker deployment on NVIDIA Jetson (ARM) systems.”

“Frontend engineer who co-built an AI-enabled marketing automation platform with multi-workspace tenancy, implementing database-scoped queries and RLS for isolation plus real-time UX (chat, voice transcription via Deepgram, autosave, Supabase Realtime). Emphasizes quality and speed through CI practices (linting/unit tests, planned Playwright) and has shipped fast iterations like Stripe prepaid card detection from overnight build through staged QA to production.”

“Data/ML practitioner with experience at Humana and Hexaware, focused on turning messy, semi-structured datasets into production-ready pipelines. Built an age-prediction model from book ratings using heavy feature engineering and multiple regression models, and has hands-on entity resolution (deterministic + fuzzy matching) plus embeddings/vector DB approaches for linking and search relevance.”