Vetted Education Professionals

“Robotics software candidate who designed and implemented a hierarchical motion-planning and whole-body control pipeline for a 37-state Spot robot to traverse complex terrain, using Graph of Convex Sets for safe footstep selection plus optimization-based IK and nonlinear trajectory optimization for joint trajectories/contact forces. Strong in optimization-heavy robotics workflows (PyDrake, MATLAB/Simulink) and methodical debugging down to signal-level and numerical stability; has not used ROS/ROS2 yet.”

“Built and shipped a production NMT system translating medical documentation for a rare/low-resource language, tackling data scarcity with retrieval-driven pattern matching plus dictionary/grammar- and LLM-based augmentation and validating quality with a linguistic expert. Also develops agentic LLM workflows with LangChain/LangGraph (including a deep-research style system) and has experience aligning medical AI deployments with clinician-defined risk metrics and human-in-the-loop decision making.”

“Animation pipeline/cinematics specialist focused on Maya-to-Unreal workflows, known as the go-to person for resolving "impossible" fringe export and data-mismatch issues (FBX versions, OS differences, tool bugs). Worked on high-profile titles including Hogwarts Legacy (proprietary cinematics module), Fortnite cinematics, LEGO 2K Racers, and Judas, supporting shots end-to-end from cloth sim pre-roll to facial/body performance alignment.”

“Robotics software engineer with ~7 years of ROS/ROS2 experience spanning dual-arm metal additive manufacturing and prior work on the DARPA Subterranean Challenge. Developed in-house multi-arm collision/trajectory planning and achieved a major calibration improvement (from ~6 cm error to ~0.5 mm) via ICP point-cloud registration, with strong simulation/digital-twin, SLAM, and deployment (Docker/CI/CD) exposure.”

“Robotics software engineer focused on real-time estimation/control and motion replanning, currently integrating a factor-graph-based estimation/control stack with sampling-based replanning in a ROS environment validated on both MuSHR hardware and MuJoCo simulation. Strong in distributed-system debugging (rosbags/logging, controlled test scenarios) and ROS performance patterns (nodelets, TF/TF2), with prior multi-robot experience from SSL RoboCup using custom UDP protocols.”

“Worked on Sophia the humanoid robot, building production animation pipelines and enhancing human-robot interaction via perception and behavior orchestration. Experienced in stabilizing noisy perception-driven state transitions and designing smooth, user-centered behavioral flows, collaborating closely with artists, animators, and experience designers to translate creative intent into measurable system behavior.”

“AI Product Manager who also operates as a product marketer/CRM lifecycle lead, focused on behavior-driven onboarding and retention. Has delivered measurable growth through segmentation, multi-channel lifecycle programs, and experimentation (e.g., activation +23%, TTFV -30%, retention +14%), and led a cross-functional chatbot integration that improved course completion (+23%) while reducing refunds (-15%).”

“Amazon engineer who built a production AI agent platform (Python/AWS Strands on Bedrock) that lets teams create tool-using, multi-agent workflows—e.g., agents that auto-triage and resolve customer support tickets by reading internal documentation and collaborating with a research agent. Previously worked in Deloitte on IAM using Ping Identity/Ping DaVinci orchestration, and applies orchestration thinking plus structured evaluation (LLM-as-judge, surveys, automated tests) to improve agent reliability.”

“Early-career (fresher) candidate who built and deployed a production AI medical document chatbot using a RAG architecture (LangChain + Hugging Face LLM + Pinecone) with a Flask backend on AWS EC2 via Docker. Has experience troubleshooting real deployment constraints (model dependencies, disk space, container stability) and setting up continuous-style evaluation with fixed query test sets tracking relevance, latency, and error rate.”

“Built ToolDreamer, a framework for selecting relevant tools for LLM agents by training a retriever on LLM-generated reasoning traces, and has hands-on experience building multi-agent systems in AutoGen (MAG-V) focused on question generation and tool-trajectory verification. Currently works as an AI-guides supervisor at Penn State, regularly communicating AI concepts to non-technical stakeholders.”

“Robotics software engineer with experience spanning embedded C++ control on microcontrollers and ROS/ROS2 production systems in automotive and marine robotics contexts (Harbinger Motors, Impossible Metals). Has deep hands-on experience debugging real-time image pipelines (DDS/QoS tuning, HIL stress testing) and building large automated test suites (1200+ tests) plus CI/CD (Dockerized Playwright tests on Jenkins).”

“Built and deployed an LLM-powered analytics assistant enabling business users to ask questions in plain English and receive validated Spark SQL executed in Databricks, with a Streamlit/Flask UI. Addressed strict client schema-privacy constraints by implementing a RAG strategy and ultimately leveraging AWS Bedrock and fine-tuned reference docs. Also has production ML pipeline experience using Docker + Airflow and AWS (S3/ECS/EC2) for financial classification models.”

“Early-career developer whose experience comes from classroom projects but has completed full end-to-end web app delivery: implemented login/search/favorites, integrated external APIs, and deployed to Google Cloud for multi-device use. Demonstrates user-centered iteration by recruiting friends to test and provide feedback, and has hands-on production-style debugging experience (e.g., resolving CORS issues during deployment).”

“Operations/process-focused leader with hands-on manufacturing and quality mindset: improved product stability by preventing oxidation via inert gas and oxygen monitoring, and implemented sensor-based automation to maintain conditions without manual intervention. Uses time studies and benchmarking to redesign workflows (reported ~60% labor reduction per batch) and trains teams on GMP/regulatory and contamination-control practices using practical demonstrations.”

“Founding engineer for an AI product (“world’s first funny AI”) who designed and implemented the full-stack architecture (React/TypeScript + Node) and migrated production from Vercel to AWS. Shipped a Lambda-based image pipeline that eliminated lag/missing images and brought page load times to under a second, and has hands-on experience integrating multiple LLM providers (OpenAI, Claude, Gemini, Grok) with structured-output and self-check reliability techniques.”

“Built and shipped an end-to-end podcast recommendation system exposed via a Flask API and React UI, explicitly balancing relevance, diversity (MMR), and safety constraints while meeting ~200ms latency targets. Also implemented a production-style RAG/information-extraction pipeline using web retrieval, spaCy NER, and fine-tuned SpanBERT with guardrails and evaluation loops (precision/recall/F1) to tune confidence thresholds and improve reliability.”

“Robotics software engineer with autonomous driving lab experience at UCSD, building and optimizing ROS2 perception and control pipelines (camera-based real-time object detection) with a strong focus on low-latency performance and robust message interfaces. Also brings production deployment experience from Hewlett Packard Enterprise, using Docker and Kubernetes for containerized environments and deployment pipelines.”

“Robotics engineer with a 2024 internship building an end-to-end software stack for an autonomous humanoid robot that follows natural-language audio commands to make coffee and deliver snacks, including perception (OpenCV), mapping, and ROS Navigation. Also contributing to a robotics foundation model effort by building data preprocessing pipelines using GroundingDINO and SAM2, and has multi-robot coordination experience with algorithms designed to handle real-world communication drops.”

“Autonomous marine surface algorithms engineer at CURLY contributing across the full autonomy stack in ROS 2 (C++/Python), from GNSS-IMU InEKF localization (100 Hz) and GTSAM object-level SLAM to semantic mapping and A*/Lie-group MPC planning/control. Strong focus on real-time optimization for constrained embedded hardware, with disciplined debugging/validation using ros2_tracing, rosbag2 replay, and Gazebo, and reproducible deployment via Docker/CI.”

“Robotics software engineer focused on autonomous drones and mobile robotics: implemented a sliding mode inner-loop controller and a RealSense T265 VIO state-estimation pipeline integrated into ArduPilot EKF3 for GPS-denied indoor flight. Strong simulation-to-deployment experience (Gazebo/MAVROS to firmware), ROS2 networking/debugging, and hands-on validation through multi-sensor trials and log analysis.”

“AI/ML engineer with production experience building an LLM-powered resume-to-job matching and feedback product using RAG, with a strong focus on latency, hallucination control, and scalable deployment. Experienced orchestrating ML inference and backend services on Kubernetes and applying rigorous evaluation/guardrail practices; also partnered with business/product stakeholders at Walmart to improve an NLP-based supplier support system.”

“Robotics software engineer/researcher with hands-on real2sim experience for deformable manipulation: led real-world data collection and diffusion policy deployment on an Aloha robot, then built a MuJoCo + Gaussian-splat digital twin with point-cloud alignment. Also brings 3 years of production software engineering experience, including Docker/CI/CD and a zero-downtime Blue-Green upgrade of a core API router, plus ROS/ROS2 work spanning autonomous vehicles and UR20 pick-and-place with MoveIt2.”

“Research-focused AI engineer who built an agentic pipeline to automatically extract Sphinx-based API documentation/changelogs and generate synthetic tasks for a dynamic LLM code benchmark targeting real-world API evolution and deprecations. Experienced with multi-agent orchestration (AutoGen, LangChain, CrewAI) and rigorous evaluation methods, and has prior multi-agent work from a Microsoft Research internship.”