Vetted Computer Vision Professionals

“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”

“Dual major in Computer Science & Engineering and Electrical Engineering who built a VR-based powered wheelchair assessment simulator with an NGO for disabled clients. Served as software/controls lead, implementing ESP32 head-array firmware (HID keyboard approach), Unity motion/physics and safety logic, and therapist-oriented scoring/logging; achieved <50ms motion variability and reduced collisions by ~50% in user trials.”

“Gameplay programmer with UE5 Blueprint-focused experience who independently shipped a multiplayer stealable XP/level progression system (including disconnect/anti-exploit handling and team-based data flow). Prototypes mechanics in Unity before recreating in Unreal, and has hands-on vehicle simulation work with a strong emphasis on modular architecture and performance-conscious UI update patterns.”

“Software engineer with hands-on hardware/software crossover work: led an EMG circuit project using PSpice simulation and MATLAB-based data processing. Also contributed to an agriculture research computer-vision effort (hens/eggs tracking), building a PyTorch inference program and boosting model accuracy by ~10–20%, plus limited ROS 2 Humble exposure on an autonomous EV model with LiDAR/camera detection.”

“Robotics lead engineer (PhD/agriculture research context) who built and iterated a three-unit, wirelessly coordinated greenhouse data-collection robot—solving real-world alignment and comms reliability issues by redesigning the rail/gear system and moving from RF to ESP Wi-Fi with MAC-addressed control. Strong embedded C/C++ background with full-stack robot control implemented from scratch; beginning exposure to ROS 2 via an upcoming field deployment.”

“Robotics engineer who built an educational/research robotic arm end-to-end, including IK/FK math, simulation-based validation, and ROS2 Humble integration with multiple teleoperation inputs (DualSense and Leap Motion). Also optimized a resource-constrained ESP32-S3 wireless maze robot to stream real-time video and sensor data over WiFi using TCP/HTTP with RTOS-based concurrency and binary struct packing.”

“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”

“Embedded/IoT-focused builder who has shipped solo projects on ESP32 + FreeRTOS, including a security camera system with a machine-vision pipeline, light-sensor-driven IR control, and Telegram-based animated GIF alerts. Demonstrated real-time debugging skills by resolving race conditions and timing issues via buffer redesign and mutex-based synchronization; no ROS/ROS2 experience yet but open to learning.”

“Engineering student with hands-on robotics and simulation experience: led an Arduino line-following “Batmobile” robot project used as a K–12 teaching tool and won best design in a 100+ student section. Also implemented SARSA reinforcement learning for a 16-DOF robotic hand in MuJoCo, optimizing the state representation to train efficiently on a CPU, and brings strong cloud/container skills (Docker, Kubernetes, AWS certs).”

“New-grad software engineer who built a real-world smart-city traffic camera/operations dashboard pitched to Peachtree Corners, GA, integrating Bosch cameras with an MQTT/Node-RED/InfluxDB pipeline and Grafana visualizations. Implemented rule-based alerts (including SMS dispatch for janitorial cleaning) and improved production reliability with queuing, redundancy, monitoring, and load testing, reaching ~99% message delivery. Actively seeking onsite, customer-facing roles with travel.”