Vetted OpenCV Professionals

“Built and deployed an on-prem, HIPAA-compliant LLM pipeline for oncology-focused clinical note generation and decision support, emphasizing grounded differential diagnosis and explainable reasoning via RAG to reduce hallucinations. Also created a LangGraph-based multi-agent academic paper search system integrating Tavily, arXiv, and Semantic Scholar with an orchestrator that routes tasks to specialized sub-agents.”

“Cloud infrastructure/product engineer with end-to-end ownership of cloud-native storage/observability products, including taking an internal CMS to Google Cloud Marketplace and scaling to ~40,000 deployments. Strong in Kubernetes-based platforms (Operators, microservices, RabbitMQ) and performance/scalability work (e.g., 200% cluster capacity increase) plus internal tooling that materially improved SRE/QA debugging and release velocity.”

“AI engineer with production experience building a high-accuracy (98%) fraud detection system operating at real-time latency (1–2s) over millions of transactions, using a multi-model pipeline approach to meet performance constraints. Also implemented Airflow-orchestrated workflows (DAGs, retries, alerts) to replace brittle cron scripts and is currently pursuing a master’s project on real-time ASL-to-text conversion.”

“Robotics software engineer with hands-on experience building a dual-arm (Kawasaki duAro) Cranfield assembly task-planning and motion-planning stack in ROS/MoveIt, using PDDL + behavior trees and OMPL for collision-free execution. Improved tight-tolerance insertions by integrating RGB-D visual servoing into the task planner loop, and also built an LLM-driven navigation pipeline with ORBSLAM3 for natural-language command parsing and real-time replanning.”

“Robotics engineer with capstone experience building an autonomous food-assembly robot arm, owning perception/deep learning (SAM2-based segmentation) and a model-based RL manipulation policy for deformable food items while also serving as project manager. As a robotics engineering intern at Salin247, optimized an autonomous farm vehicle perception stack to hit 20 FPS by cutting latency from 200ms+ to ~40ms using GPU acceleration (CUDA OpenCV, CuPy) and multiprocessing, and built ROS 2 nodes for real-time perception and streaming.”

“MSR robotics candidate who led a 4-person project building a ROS2 MoveIt wrapper for a Franka Emika arm and integrating a RealSense-based vision pipeline for color-based object tracking/sorting. Also building a quadruped with ROS on Raspberry Pi, bridging ROS commands through a motor driver to TTL-controlled motors, and expanding from Python ROS development into C++ for navigation/LiDAR/SLAM work on TurtleBot3.”

“Unity VR/MR developer with multiple shipped Meta Quest projects, including a multi-user mixed-reality co-creation experience featuring real-time connection logic and shader-driven mesh generation for performance. Also builds AI-powered interactive applications, recently creating a video interview simulator using OpenAI API, HeyGen real-time avatars, and AWS audio/agent tooling while managing end-to-end latency challenges.”

“Robotics software engineer focused on real-time mapping and SLAM in unstructured environments, combining camera-based navigation, GTSAM/iSAM2 pose-graph optimization, and nvBlox ESDF mapping with strong real-time performance on both RTX 4070 and Jetson Orin. Has hands-on ROS 2 + Docker integration experience and has built Isaac Sim plugins/ROS 2 packages to make LIO-SAM work in simulation, plus work on decentralized multi-robot SLAM with heterogeneous LiDARs and edge map building.”

“ML/LLM engineer who built production systems to speed up artist content-creation workflows, including a fine-tuned image captioning model paired with a RAG layer over image embeddings/captions to improve consistency across changing domains. Experienced orchestrating multi-tool agents with LangChain/LangGraph (planning + critic/reflection) and setting up practical monitoring (caption rejection rate) plus evaluation sets for tool-calling accuracy, output quality, and latency.”

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

“Robotics software engineer who led localization/SLAM work on an autonomous indoor security drone operating in a pre-mapped environment. Implemented a robust localization strategy combining visual PnP loop closures with point-cloud ICP to mitigate issues like visual map aging, and uses ROS tooling (rosbag/TF/RViz) plus Gazebo and Docker for repeatable debugging, simulation, and development.”

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”

“Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.”

“Robotics software intern (Summer 2025) at Ola Krutrim working on 2W/4W ADAS: integrated an ASM330LHH IMU over I2C, performed camera-LiDAR intrinsic/extrinsic calibration, built an interactive calibration GUI, and optimized a camera-LiDAR fusion pipeline (cut latency from ~500ms to ~200ms) including CUDA parallelization and Kalman filter-based lane tracking. Strong ROS 2 background with URDF/Gazebo simulation and custom ROS2 Arduino bridge work for hardware control.”

“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).”

“Robotics software engineer/researcher at Stanford PDML Lab building VisualFT, a ROS2-based visual-tactile sensing system for compliant force-control guidance in acupressure/ultrasound-style manipulation. Also interned at Neocis (dental robotics) improving safety-critical collision detection using Bullet Physics with automated validation and CI (Jenkins/CDash).”

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

“Summer SDE intern at AWS who built and deployed a column-lineage debugging tool for on-call engineers, using AWS Bedrock to parse SQL and generate a column DAG. Integrated the tool into an existing validation system and hardened it against real-world SQL format differences via flexible parsing and testing with queries from multiple upstream teams.”

“AI/LLM engineer with Fidelity Investments experience who built and shipped a production GraphRAG system that augmented prompts with codebase context, improving business analyst efficiency by 15% and saving ~$3.5M annually. Strong in AWS EKS/Kubernetes/Helm and enterprise IAM/OIDC patterns (including cross-account S3 access), with experience mentoring interns and collaborating with non-technical leaders to extend AI pipelines (e.g., adding SQL functionality during MVP).”

“Backend-focused full-stack engineer who built an MVP at Neon AI for PhD students: a FastAPI backend integrating multiple cloud and local LLMs plus a RAG pipeline with session/identity management, designed to be modular and extensible across domains. Also has VMware experience debugging production issues and executing safe, API-compatible refactors with staged rollouts and strong security controls.”