Vetted Gazebo Professionals

“AI/ML engineer focused on real-time, production-grade LLM systems, with a robotics-adjacent mindset around latency/accuracy tradeoffs and modular pipelines. Built a scalable RAG-based assistant orchestrated as microservices on Kubernetes with Kafka async messaging, ONNX/quantization optimizations, and monitoring (Prometheus/Grafana), citing a ~35% hallucination reduction; has also experimented with ROS Noetic/Gazebo to understand ROS concepts.”

“Master’s robotics candidate at Northeastern (Silicon Synapse Lab) who built and tuned an NMPC for the M4 multi-modal morphobot to achieve high-speed (>10 m/s) aggressive flight maneuvers and even hover under a full rotor failure, using MATLAB/CasADi/Simulink/Simscape with IPOPT. Also has ROS/ROS 2 experience spanning SLAM/navigation on a UGV and GPS/IMU sensor-fusion + dead-reckoning with custom ROS 2 nodes/messages, with a strong simulation-first and real-time debugging approach.”

“Robotics software engineer with hands-on ROS 2 autonomy experience on an obstacle-avoiding quadrotor (ROS 2 + Gazebo + PX4 + Nav2/SLAM), including custom work to extend Nav2 into a 3D aerial domain and output PX4 trajectory setpoints. Also built cost-saving ML infrastructure (PostgreSQL + AWS data-cleaning pipeline) and improved object detection accuracy by 40% using CUDA/PyTorch, with strong containerization and CI/CD practices (Docker + Kubernetes, aggressive version pinning) to prevent environment drift.”

“Robotics software engineer with deep ROS/ROS 2 autonomy experience across warehouse fleets (Knapp delivery robots and quadrupeds), spanning SLAM, EKF-based sensor fusion localization, Nav2, and behavior-tree mission orchestration. Built a simulation-first testing approach using Isaac Sim Replicator with Dockerized, statistically analyzed repeat runs to catch nondeterminism, and personally owned real-world validation. Also developed a custom UR10 singularity-check ROS node based on manipulability.”

“Backend/DevOps engineer pivoting into robotics/space, building hands-on ROS2 (Humble) skills via Gazebo simulations and experimenting with Nav2 and slam_toolbox. Brings strong distributed-systems and real-time debugging practices (profiling, instrumentation, QoS/retry patterns) and is actively learning perception and control fundamentals to transition into autonomous robotics.”

“Robotics software candidate with experience spanning simulation (MuJoCo, Gazebo, Webots) and ROS1/ROS2 development, including hardware-oriented work on a hexapod and a Mecademic Meca500 R3 arm. Built a visually guided interactive indoor robot system using a CV pipeline plus POMDP + imitation learning with PPO-based residual RL, and has practical debugging experience improving LiDAR SLAM stability and migrating sensor interfaces from ROS1 to ROS2.”

“Robotics software engineer with hands-on ROS2 + Autoware perception experience, focused on building benchmarking infrastructure for object detection models inside a real-time autonomous driving stack. Strong in evaluation rigor (synchronization, deterministic playback, format standardization) and practical ROS2 debugging/validation workflows using RViz and Gazebo.”

“Robotics software developer with hands-on ROS experience building a timer-driven closed-loop controller for a differential-drive robot in Gazebo, including square/figure-8 trajectory planning and RViz/rqt_graph-based debugging. Currently extending the system with LiDAR-based obstacle detection, safety overrides, and reactive velocity arbitration for collision-free motion.”

“Robotics software developer building an ESP32/FreeRTOS wheel-encoder driver for a differential-drive robot with PID velocity control and ROS2 odometry publishing. Has implemented vision-based human tracking (DepthAI) and an obstacle map + EKF sensor fusion using IMU and LiDAR, with a simulation-first debugging workflow (Gazebo, Foxglove) and Dockerized environments; plans to extend to Nav2 + SLAM Toolbox for building-scale mapping.”

“Robotics software engineer/researcher (master’s work) who built a human-aware motion planning stack for a UR16/UR16e arm: RGB-D 3D skeleton perception in ROS2, deep-learning-based human motion prediction, and MoveIt2-integrated real-time planning with a Gazebo digital twin. Demonstrated strong real-time optimization (profiling + GPU offload with CuPy/TensorRT) and practical systems skills spanning safety validation, visualization, and low-level comms (CAN/SocketCAN) on embedded deployments (Jetson, Docker, Autoware/Ouster).”

“Robotics software engineer with real customer deployment impact at Dematic, improving AGV front-guided steering, localization sensor fusion, and control-loop performance while integrating with Beckhoff PLC safety systems. Also built a multi-robot ROS milling cell in graduate work, combining URDF/Gazebo simulation, MoveIt/OMPL planning, ROS performance profiling, and CNN-based defect detection to drive coordinated robotic milling.”

“Robotics/AV engineer with strong ROS2 and autonomy stack integration experience, including bringing Autoware Universe up on a real Lexus autonomous vehicle platform. Also built a hierarchical reinforcement learning proof-of-concept for Boston Dynamics Spot (navigation + manipulation) and tackled sim-to-real challenges by implementing PD torque conversion for Jetson-based hardware; improved localization accuracy via GNSS+EKF fusion with a reported 28% drift reduction.”

“Robotics software researcher who led a Boston Dynamics SPOT project on non-prehensile manipulation of heavy boxes, combining MuJoCo-based RL, ViT-based perception, and SPOT SDK control; the work is under review for ICRA 2026. Also built a ROS planning-and-learning stack on a LoCoBot using PDDL task planning, RTAB-Map SLAM, MoveIt motion planning, and RL to recover from execution failures.”

“Robotics software engineer focused on production-deployed industrial automation, owning robot behavior end-to-end across integration and production support. Has hands-on experience coordinating multiple robots with PLC safety, conveyors, and vision, using state-machine orchestration, deep debugging (logging/I-O tracing), and performance tuning to achieve stable run-at-rate operation. Also builds ROS/ROS 2 distributed systems in C++/Python and tunes DDS/QoS for reliable multi-machine communication.”

“Robotics software engineer who worked on NYU’s Medi Assist robot, owning navigation sensor bring-up (LiDAR/radar/IMU) and SLAM stability, plus delivering a safety-critical braking system. Built a YOLOv8 perception pipeline on Jetson Nano and wrote STM32 firmware to actuate brakes, achieving ~50ms reaction time, and implemented diagnostics/health checks and reliable inter-board comms (ROS2 + UART with checksums/heartbeats).”

“Robotics software engineer focused on ROS2 autonomy, with hands-on work building a monocular visual odometry system on KITTI (including GPS-based scale correction and RViz trajectory visualization) and an end-to-end Gazebo simulation integrating URDF, slam_toolbox, and Nav2. Demonstrates strong practical debugging skills around TF frames, lifecycle nodes, and Gazebo plugin/version compatibility.”

“Robotics software engineer who led development of a vision-based end-effector stability/vibration analysis tool using phase-based motion magnification and frequency-domain analysis (FFT/Bode) to uncover resonances missed by motor-only diagnostics. Experienced with ROS 2 C++ perception/navigation (ArUco + PnP) and real-time industrial integration, including optimizing a 1 kHz EtherCAT/Beckhoff PLC/Modbus TCP diagnostic pipeline and designing deterministic interfaces across heterogeneous subsystems.”