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Vetted Computer Vision Professionals
Pre-screened and vetted.
Michael Knott
Executive CTO specializing in AI, FinTech, robotics, and regulated platforms
“CTO/co-founder who spent the last 6 years running a Singapore venture studio (Undercurrent Capital), performing technical and business due diligence and leading ventures from ideation through growth. Notably built a MAS-regulated bond issuance platform (Cache) for a commodities brokerage, integrating onboarding, back-office, margin calls, and regulated money flows, attracting $120M USD in the first month.”
Mid-level Data Scientist specializing in ML, data engineering, and real-time analytics
Mid-level Data Scientist specializing in Generative AI, RAG systems, and MLOps
Mid-Level Software Engineer specializing in full-stack and AI/LLM evaluation
Intern Full-Stack Developer specializing in AI and web applications
Junior Full-Stack Software Engineer specializing in distributed systems and scalable platforms
Mid-level Software Engineer specializing in backend, full-stack, and network automation
Senior Engineering Director specializing in Generative AI, XR, and gaming platforms
Junior Engineering Technician specializing in product development, CAD, and robotics
Senior Software Engineer specializing in robotics, computer vision, and scientific instrumentation
Mid-level AI Engineer specializing in LLM agents and production ML systems
Executive AI Architect specializing in low-power edge/embedded AI systems
Dhruv Kamalesh Kumar
Mid-level Generative AI Engineer specializing in LLM agents and RAG applications
“GenAI builder and technical lead with ~2 years of hands-on production experience, including GENIE (a GenAI sandbox for ~44,000 Massachusetts public-sector employees) and A-IEP, a multilingual platform helping parents understand complex IEP documents (cut processing from ~15 minutes to ~2 and used by 1,000+ parents). Strong in RAG/agentic architectures, AWS serverless + Step Functions orchestration, and rigorous evaluation/guardrails for reliable real-world deployments.”
Sahil Gupta
Junior AI Software Engineer specializing in LLM agents, RAG, and healthcare NLP
“Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.”
Hemanth Katikala Muniraj
Intern Robotics Software Engineer specializing in ROS2 autonomy and LiDAR localization
“Robotics software engineer focused on production-grade autonomous mobile robot (AMR) navigation in warehouse-style environments, with deep hands-on ROS2/ROS Noetic experience across SLAM, AMCL/NDT LiDAR localization, and Nav2 integration. Strong in real-time debugging and performance tuning using rosbag-driven regression workflows, plus containerized deployment (Docker/Compose) and distributed robot/edge-device communication via MQTT/REST.”
Nash Boisvert
Senior Full-Stack Software Developer specializing in web, mobile, and cloud platforms
“Frontend engineer who built a live sports games hub end-to-end: ingesting and normalizing data from 4 external APIs, populating a high-volume live table, and delivering a real-time WebSocket-driven React/TypeScript dashboard. Strong on scalable architecture (SOLID, layered design, queues), performance/load testing with Docker, and startup-style ownership across code review, QA, and staged rollouts to web and app stores.”
Mohan Pushadapu
Mid-level Mechatronics Engineer specializing in robotics, embedded firmware, and autonomous systems
“Robotics/embedded engineer with hands-on firmware ownership for closed-loop motor/vision systems and strong ROS1 navigation experience (move_base, gmapping, robot_localization), including EKF sensor fusion to eliminate localization drift to sub-10cm accuracy. Also brings IoT distributed pub/sub expertise (30+ devices over MQTT, 99% uptime) plus Unity AR/VR simulation and computer-vision test automation that saved 100+ hours.”
Joshua Sylvester
Senior Machine Learning Researcher/Engineer specializing in temporal modeling and production ML systems
“Backend engineer who built and evolved a startup data-processing backend (Express.js/MySQL) handling millions of user data points, with a microservices pipeline integrating multiple social media APIs. Emphasizes reliability and security through comprehensive testing, robust error/retry handling for sequential pagination constraints, and tight IAM/JWT/OAuth-based access controls.”
Serge Alhalbi
Mid-level Robotics & AI Engineer specializing in autonomous systems
“Robotics software engineer with deep ROS2 experience who owned the perception stack for an automated C. elegans manipulation system—building YOLO-based worm segmentation plus OCR label reading and integrating it into a MoveIt2 pipeline with real-time latency constraints. Also deploying ROS2 on an AgileX Tracer with ZED depth camera for vision-based person following and working on SLAM/sensor fusion, with additional production-style ML deployment experience (Dockerized FastAPI + PyTorch on AWS EC2 with CI/CD).”
Dara McNally
Junior Computer Vision Researcher specializing in deep learning and object detection
“Robotics engineer who built and scaled a distributed perception stack on a Unitree Go1 quadruped, coordinating 5 Jetson Nanos and a Raspberry Pi to capture, aggregate, and stream multi-camera video in real time via UDP/GStreamer and custom ROS nodes. Also implemented a YOLOv9-based detection pipeline enhanced with Grad-CAM-driven selective image enhancement (e.g., MIRNet/UFormer) to improve real-time detections and robot reactions to visual stimuli.”
Pranathi Kamisetty
Intern AI Engineer specializing in LLMs, NLP, and conversational search
“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”
Anupreet Singh
Intern Full-Stack Software Engineer specializing in AI and backend systems
“AI intern who built core pieces of Cyberdome, a full-stack agentic compliance automation product using Next.js, Python, RAG, Qdrant, and NIST control retrieval. Stands out for combining frontend product work with backend LLM infrastructure, on-prem/local model deployment, and practical iteration based on user trust concerns around proprietary data.”
Nikhil Tatikonda
Intern AI/ML Engineer specializing in LLM agents, RAG, and automation workflows
“AI automation builder who shipped an OpenAI-powered weekly "trending AI tools" WoW reporting system (65 categories) that reduced a 6–7 hour manual process to ~10 minutes at negligible API cost. Also building a RAG-based content creation prompt engine that turns PDFs into storyboards with fact-checking/traceback to source lines, plus experience with AWS deployment components (Lambda, ECR, App Runner, Bedrock, API Gateway) and GitHub Actions.”