Vetted Object Detection Professionals

“Backend-focused engineer who built a Python-based automation system leveraging Gemini AI and prompt-driven PDF field extraction to replace a previously manual third-party workflow. Drove stakeholder alignment around accuracy/acceptance thresholds and added production-minded safeguards like graceful failure handling and backup model contingencies.”

“Backend engineer with experience modernizing legacy systems and building modular Python/Flask services, including a REST-to-GraphQL migration for an e-commerce platform that improved API response time by 45%. Strong in performance and scalability work across PostgreSQL/SQLAlchemy (indexing, JSONB, N+1 fixes, connection pooling) and high-throughput systems (Celery + Redis), plus integrating ML microservices with TorchServe, Kafka streaming, feature stores, and Prometheus/Grafana monitoring.”

“Robotics software engineer who built a ROS 2 Humble autonomous hospital-equipment detection/localization robot end-to-end in Gazebo (custom worlds/models, Nav2 waypoint navigation, YOLOv8n perception, TF2-based depth fusion) and solved real-time integration issues via multithreading and QoS tuning. Also implemented and tuned an MPPI controller to enable smooth reverse parking on an OpenPodCarV2 platform, including real-world reverse engineering and hardware/software debugging.”

“Master’s thesis engineer who built and deployed a continuous real-time perception + state estimation + control loop under tight latency constraints, owning both software architecture and hardware integration. Strong ROS 2 fundamentals with a systems-first approach—stabilizes robotic behavior by instrumenting, logging/replaying real data, and fixing timing/synchronization issues rather than treating failures as purely algorithmic.”

“Robotics engineer focused on simulation, modeling, and control, with hands-on sim-to-real experience from a soft, foldable “grasshopper” robot where friction/contact physics and servo dynamics drove real-world performance gaps. Built a ROS 2 voice-operated TurtleBot system integrating YOLOv5 + stereo depth for object picking with an attached arm, and debugged AMCL/SLAM to cut localization error from 10–13 cm to ~5 cm. Currently developing a quadruped in MuJoCo with a 3-layer control stack (RL + MPC + PD) and an RL training pipeline in JAX ahead of hardware.”

“Master’s capstone at Stevens: conceptualized and helped build a cross-platform assistive mobile app for visually impaired users with currency detection (ML), voice-driven AI chatbot (OpenRouter), and a guided navigation video-call feature using a shared room code. Personally implemented Firebase login/sign-in, facial-recognition login, video calling, chatbot integration, and led integration/testing across the full app.”

“Robotics software engineer with thesis work optimizing the Autoware perception pipeline via DDS/synchronization tuning for lower latency and better throughput, plus hands-on ROS1/ROS2 experience deploying perception (YOLOv8) and SLAM/localization on real vehicles and delivery robots. Has practical debugging depth (Kalman filter crashes, transformation/scan-matching issues) and CI/CD automation experience with Jenkins.”

“PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.”

“Robotics engineer leading development of a Physical Reservoir Computing controller for a pneumatic soft robotic arm, owning everything from automated data collection and leak-testing automation to hardware design/manufacturing and cross-lab integration with Virginia Tech. Built ROS 2/DDS-based multi-robot systems integrating OptiTrack, a lab quadruped, and a UR5e, and pairs simulation (Gazebo/MuJoCo) + PPO RL training with production-ready tooling (Docker, CI/CD, Flask dashboards, RAG chatbot portfolio).”