Vetted Artificial Intelligence Professionals

“Has worked at a startup within an incubator program and is a certified mentor with a startup mentorship non-profit focused on early-stage/pre-funded companies. Not currently seeking to found a company or take equity-only roles, but open to working at very early-stage companies (pre-launch/pre-revenue/pre-funded).”

“Sales candidate with 35 years of experience who expressed interest in AI and shared a resume link and LinkedIn profile, but did not provide any concrete deal examples or details about outbound prospecting or recent closes during the screen.”

“Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).”

“Robotics software engineer with a Master’s thesis building an end-to-end monocular-vision pick-and-place controller for construction use cases on TurtleBot3 + OpenManipulator, spanning synthetic data creation, transfer learning, simulation in Gazebo, and real-robot deployment. Leveraged ROS distributed architecture to run two heavy AI models across networked GPUs to achieve usable real-time performance, and has production CI/CD experience as a Senior Software Engineer in AI/analytics.”

“Robotics engineer who built a smart campus tour robot on a Kobuki Turtlebot using ROS 1, implementing a full navigation stack (semantic world model, A* planner, tour executor, path follower) and integrating SLAM (gmapping) plus a hybrid reactive safety controller. Experienced taking systems from Gazebo simulation to real hardware, including extensive real-world debugging and Docker-based development to handle ROS/Ubuntu version constraints; planning a move to ROS 2 on Turtlebot 4.”

“Unity VR/AR developer with industrial training simulation experience (heavy machinery, electrical panel, arc welding) who improved user completion and retention by shipping a context-aware AI instructor. Uses Unity Analytics and in-game feedback to pinpoint drop-offs and drive measurable gains (e.g., 30%→75% completion; 60% drop-off fixed to reach 85%). Has also built multiplayer collaborative training prototypes with Photon PUN2 and strong Git/Unity workflow practices to reduce scene conflicts and technical debt.”

“Software engineer and University of Chicago graduate teaching assistant who built a full-stack internal analytics dashboard (React/TypeScript + Node/Express) and worked in RabbitMQ-based microservices with Prometheus/Grafana observability. Also created an AI-powered ERD diagram generator (React + MermaidJS + OpenAI) adopted by students to save hours on database assignments, using validation loops to ensure valid Mermaid output.”

“Built and deployed a production LLM-powered email assistant (“wood flow”) for a local pet resort to automate after-hours inbound email handling, including email categorization and context-aware auto-responses. Uses n8n for orchestration and applies CRISP-DM, load/edge-case testing, and RAG-based context retrieval, and has experience presenting AI solutions with budgeting and ROI to a non-technical founder.”

“Post-graduate, self-directed robotics/RL practitioner who independently built a modular reinforcement learning training framework in Python using Stable-Baselines3, Gymnasium, and PyTorch. Emphasizes reproducible experimentation (multi-seed validation), simulation (PyBullet/Box2D), and systematic comparison of algorithms/environments via a factory-pattern architecture.”

“Robotics/perception engineer with experience at Magna International building and scaling a ROS2-based autonomous vehicle sensor-fusion stack from radar+camera to include LiDAR, addressing hard problems like PTP nanosecond synchronization and probabilistic data association. Also developed and deployed a real-time 3D LiDAR object detection pipeline (PointPillars-style) optimized with ONNX/TensorRT and FP16, with strong production bringup/monitoring and rigorous simulation-to-road testing practices.”

“Application/security-focused customer-facing implementer who has secured multi-customer data aggregation apps using per-tenant isolation, short-lived/scoped tokens, and vault-based secrets management. Troubleshoots production issues via API gateway logs and performance tuning, and runs repeatable onboarding playbooks with strong customer-specific and cross-project documentation. Emphasizes AWS least-privilege IAM and secure agent deployment patterns, plus container scanning practices that catch vulnerabilities pre-production and build developer trust.”

“Data/ML and product leader with large-scale consumer and enterprise experience (including Walmart) who blends hands-on prototyping with executive stakeholder alignment. Has delivered measurable outcomes across personalization, semantic search/knowledge graphs, and fraud/security architecture, and has scaled organizations rapidly (30→180 in 12 months) by upskilling and building modern data/ML engineering capabilities.”

“Entrepreneurial product builder who created chaintrigger.com in response to early Web3 demand for real-time on-chain event reactions, offering an alternative to The Graph Protocol and achieving adoption among games and other Web3 projects. Currently developing new tools, dogfooding internally, and building distribution via personal network and a niche Twitter/X following to gather feedback and iterate quickly.”

“Product-focused candidate with live B2C/product-led growth experience who translates free-to-play game mechanics (onboarding as a core loop, progressive unlocking, nudges, variable rewards) into real-world web/mobile products. Strong in live experimentation, KPI-driven iteration, and monetization/retention measurement (DAU/MAU, funnels, LTV-focused A/B testing).”

“Founder building AdaptiveWorX™ Flow, a graph-native, agent-first operating system intended to replace document-driven/Agile-era workflows with continuously verifiable, causally linked delivery. Brings decades of systems/architecture perspective plus prior digital health experience, including a PoC turning behavioral therapy sessions into structured longitudinal data using real-time A/V capture and multimodal AI, with an emphasis on compliance, traceability, and scalable platform design.”