Vetted OpenCV Professionals

Deepam Ameria

Screened

Intern Robotics Software Engineer specializing in autonomy, perception, and control

Los Angeles, CA2y exp

“Robotics software engineer with hands-on experience building autonomy features across perception, planning, and systems integration—most notably for an autonomous lunar rover that detects and geometrically models craters to plan terrain manipulation. Also owned development of an autonomous stair-climbing module for a quadruped robot as an intern, and has real-time motion-planning/IK debugging experience on a Franka Panda using RGB-D (RealSense).”

Samuel Ehrenstein

Screened

Mid-level Computer Vision & ML Researcher specializing in medical imaging and 3D vision

Chapel Hill, NC4y exp

“PhD (CS) candidate with hands-on autonomy and robotics experience: improved safety-critical behavior for Kodiak’s self-driving 18-wheeler trucks, increasing overtaking clearance by ~2 feet and reducing safety alerts. Also debugged a C++ SLAM system for 3D colon reconstruction and built a low-budget distributed simulation cluster using Linux, Docker, and Python, plus implemented multi-hop SSH-based comms for an underwater robotics competition minibot.”

“Robotics software engineer who has built full ROS 2 stacks for both a semi-automated robotic ultrasound system (UR5e + depth camera) and a quadrotor planning/MPC pipeline in Gazebo. Strong in integrating major ROS 2 frameworks (MoveIt/Nav2/RTAB-Map), writing custom packages (URDF, ACADOS-based MPC, laser landmark detection), and optimizing real-time behavior via GPU parallelization and distributed multi-threaded ROS 2 architectures; also contributes to ROS 2 core (structured parameters).”

Akashleena Sarkar

Screened

Junior Software Engineer specializing in robotics and real-time distributed systems

Mountain View, CA2y exp

“Robotics software engineer focused on low-compute navigation/SLAM: built a 6-DOF SLAM validation pipeline (IMU + 2D LiDAR + ultrasonic) producing ~1cm OctoMap accuracy and deployed it on an Intel Atom by optimizing particle-filter SLAM with a greedy max-likelihood update. Deep ROS 2 experience (executors, composable/lifecycle nodes, QoS, timestamping) plus simulation and deployment tooling (Gazebo C++ plugins, Docker, CI/CD, ROS 2 build farm) and drone navigation work with MAVROS/PX4.”

“Graduate robotics researcher (Georgia Tech/Georgia Tech Research Institute) who helped modernize the Georgia Tech Robotarium by migrating its comms stack from MQTT to ROS2 across MATLAB/Python and updating embedded Teensy firmware for new sensors. Currently validating ToF distance sensors and integrating IMUs, with planned GTSAM factor-graph SLAM sensor fusion; also debugged and improved a decentralized coverage-control algorithm at swarm scale (1000–2000 agents) using computational geometry and literature-backed methods.”

Ho-Wei Lu

Screened

Junior Robotics Engineer specializing in motion planning and control

Berkeley, USA1y exp

“Robotics software engineer who built a ROS2-based ping-pong ball interception system on a 7-DOF Sawyer arm, spanning real-time vision, trajectory prediction, and an MPC joint-velocity controller to hit a flying ball within ~1 second. Demonstrated strong real-time debugging and systems integration skills (timestamp-based latency analysis, event-based redesign, ROS2 QoS tuning) and is currently working with Isaac Sim in Docker with GitHub-based CI/CD for assembly-task simulation.”

“Robotics software engineer leading an autonomy stack migration from ROS1 to ROS2, including a custom-built global parameter server to preserve existing infrastructure while shipping continuous production releases. Hands-on across navigation/safety/monitoring packages, control (ROS2 PID for steering/speed), and localization performance work (particle filter optimization), with strong ownership of CI-driven test strategy and release quality.”

“Data Analyst at U.S. Cellular who built production LLM solutions, including a Tableau-embedded chatbot that converts natural language questions into Oracle SQL and returns actionable KPI insights for non-technical users. Also authored MAD-CTI, a multi-agent LLM system for dark web hacker forum threat intelligence (published in IEEE Access) that outperformed single-agent approaches by 14%.”

“Applied LLMs and a graph-RAG architecture in Neo4j to automate an accounting firm's cross-checking of transactional books against tax regulations, indexing 1,000+ pages into a knowledge graph with vector search. Combines agentic LLM workflows with classical NER (Hugging Face/NLTK) and validates using expert-labeled held-out data plus precision/recall and measured accountant time savings after deployment.”

Pratik Jaiswal

Screened

Mid-level AI/ML Engineer specializing in financial services ML and MLOps

Remote, USA4y exp

“ML engineer/data scientist with M&T Bank experience who built a production reinforcement-learning portfolio analytics tool for wealth management, emphasizing near real-time performance via batch/serving separation and robust generalization through stress-scenario backtesting and RL regularization. Strong MLOps background (Airflow, Grafana, MLflow) and proven ability to drive adoption with non-technical stakeholders using KPI alignment and SHAP-based explanations.”

“Backend/data engineer with hands-on production experience across FastAPI/PostgreSQL APIs and AWS (Lambda, ECS) delivered via Terraform + GitHub Actions. Built Glue-based ETL pipelines into Redshift with schema evolution and data quality checks, modernized legacy reporting into Python microservices, and has demonstrated measurable SQL performance wins (multi-second query reduced to sub-300ms).”