Vetted Object Detection Professionals

“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”

Parvesh Garg

Screened ReferencesStrong rec.

Unity Team Lead specializing in multiplayer games and AR/VR

Greater Noida, UP, India14y exp

“Unity gameplay programmer with Photon-based multiplayer experience who built a real-time player feedback system (instant animation/VFX/audio + score updates) using events/ScriptableObjects to keep gameplay and UI decoupled. Has tackled movement desynchronization under variable latency with client-side prediction/interpolation and uses AI tools to speed up prototyping and balancing for a procedurally generated, math-based casual game.”

“Robotics software engineer from Bigbot who led localization and perception for an outdoor autonomous delivery robot, building ROS2/Nav2-based autonomy with EKF sensor fusion (IMU/odometry/GPS) and perception-driven dynamic costmaps. Experienced taking systems from Gazebo simulation to real-robot deployment, optimizing real-time behavior via logging-driven debugging and latency reduction, and integrating heterogeneous comms (MAVROS/MAVLink, UART/CAN, MQTT) for distributed and multi-robot setups.”

Zueva Tatiana

Screened ReferencesStrong rec.

Senior Software Engineer specializing in XR, 3D systems, and computer vision

Russia5y exp

“XR/Unity engineer with hands-on ownership of high-performance 3D reconstruction and visualization systems, including a Gaussian Splatting pipeline that improved target-device performance from ~20 FPS to 60+ FPS. Also brings multiplayer XR experience with Photon Fusion, cross-platform Quest/mobile shipping experience, and AI-driven NPC dialogue integration using a self-hosted rule-based backend. Based in Moscow and open to remote work across time zones.”

“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”

“Robotics/embedded developer with hands-on ROS 2 and micro-ROS experience on ESP32, building a remote-controlled high-power LED system. Worked across power distribution (buck-boost constant 30V), sensor calibration with real-time data checks, and long-range WiFi connectivity using an omnidirectional antenna achieving 100m+ coverage.”

Siddhartha Geddam

Screened

Junior Robotics/ML Engineer specializing in autonomous UAVs and perception

2y exp

“Machine learning robotics engineer with internship experience deploying object detection and semantic segmentation models to an autonomous vehicle fleet operating in airports and naval docking stations, optimizing with ONNX/TensorRT for NVIDIA Jetson edge deployment. Also built ROS/ROS2-based decentralized multi-drone coordination (TF trees, shared telemetry) validated in Gazebo and networked via Nimbro with sub-10ms latency messaging.”

“Built GynAI, an end-to-end maternal clinical decision support platform for OB/GYN practices and hospitals in North America, combining predictive ML with RAG-based LLM explainability. The candidate emphasizes real production ownership across experimentation, deployment, monitoring, and iteration, with reported impact including fewer delayed interventions in high-risk pregnancies and a 15-20% reduction in false positives.”