Vetted Education Professionals in the Bay Area

“Research-oriented ML engineer/scientist with deep experience applying generative models, adaptive optimization, and HPC infrastructure to complex physics analyses. Built reusable Python-based tools that replaced expensive Monte Carlo workflows, integrated across HTCondor/SLURM environments, and reduced analysis timelines by 2x while supporting broader team adoption and training.”

“Robotics engineer/researcher from Stanford’s Assistive Robotics and Manipulation Lab who built a custom tactile-sensing gripper system and ROS 2 data pipeline to classify the number of thin material layers grasped using a transformer-based model. Has internship experience at Motiv Space Systems building ROS 2 hardware abstractions for BLDC motor dynamics simulation, plus hands-on SLAM and manipulation work in Gazebo/MoveIt-based projects.”

“Healthcare product leader with deep oncology and pharma experience who has built both foundational clinical data platforms and AI-powered patient engagement workflows. Particularly notable for combining rigorous data standardization, LLM evaluation/guardrail design, and human-centered communication changes that drove measurable medication refill and adherence improvements. Also teaches AI to product managers and business analysts, bringing a pragmatic, education-first view of human-centered AI adoption.”

“Engineering leader with deep hands-on experience across eCommerce, retail commerce, regulatory tech, and IP PBX systems, including building a no-code web application platform. Has managed organizations of up to 65 people while staying involved in architecture and production debugging, and cites measurable impact such as 50% efficiency gains, 100% productivity improvement, and 90% error reduction through partner/API remediation.”

Manaswini Gogineni

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Backend engineer at Electric Hydrogen who built a serverless device-log ingestion and processing platform in Python/Flask, scaling throughput (4x peak ingestion) while keeping sub-300ms API latency. Strong in Postgres/SQLAlchemy performance (partitioning, materialized views) and production ML integration (ONNX model served via FastAPI microservice with async batch inference, Redis feature caching, and drift monitoring via S3/Lambda). Experienced designing secure multi-tenant systems with schema-per-tenant isolation and KMS-backed encryption.”

“Robotics/embedded builder who trained an aviation-specific LLM and deployed it offline on an NVIDIA Jetson for an in-flight voice assistant, solving performance and cabling constraints with NVMe storage and Bluetooth. Also has hands-on Raspberry Pi/Arduino robot builds (including a cigarette-butt picking prototype with hydraulic actuation) plus Docker-based FEA work using FEniCS/Gmsh and strong CI/CD + automated testing practices.”

“Built and deployed a production RAG-based semantic search and summarization system for large legal/technical document sets, owning the full backend (embeddings, vector store, chunking, prompting) and driving a reported 40–60% reduction in manual review time. Experienced with LangChain/LlamaIndex plus Airflow/Temporal-style orchestration, and applies rigorous evaluation/monitoring (A/B tests, drift detection, staged rollouts) to keep agentic systems reliable. Also partnered with a supply-chain manager at TE Connectivity to deliver an AI inventory recommendation tool projected to drive millions in value.”

“Robotics software engineer with Stanford coursework and Georgia Tech research experience, focused on end-to-end autonomy for mobile manipulation and real-time planning under uncertainty. Built a ROS 2 LoCoBot system combining Gemini speech-to-text, YOLO-based RGB-D perception, navigation, and grasping with robust synchronization/TF fixes, and developed an information-theoretic UGV planner for radiological source localization validated via Monte Carlo simulation.”

Seongjae Ahn

Screened

Intern/Junior Robotics & Controls Engineer specializing in simulation, teleoperation, and diffusion policies

Berkeley, CA2y exp

“Robotics software engineer focused on simulation-to-teleoperation pipelines in NVIDIA Isaac Lab/Isaac Sim, including custom Dynamixel motor control integrated with USD/physics for dataset collection. Has hands-on ROS2 Humble + MoveIt2 integration for UR + Robotiq in Omniverse and builds Docker/CI workflows for GPU-enabled robotics stacks; also brings MPC coursework and multi-robot ocean drone comms experience (XBee/I2C).”

“Built and productionized a dual-agent LLM invoice-processing system for GFI Partners, adding guardrails and audit trails to earn stakeholder trust and drive adoption while cutting operational burden by 75%. Uses LangSmith observability to diagnose real-time workflow regressions and has experience teaching agentic AI concepts (e.g., at Carnegie Mellon) through hands-on, scaffolded demos.”

“Built and shipped a map-embedding SDK (published to npm) for Walmart apps, solving key performance issues with real-time streaming (WebSockets) and Canvas rendering while prioritizing developer experience. Also applies LLM/agentic patterns in production workflows—using diagnostic agents and human-in-the-loop escalation to detect and resolve issues (e.g., voice agent loops caused by RAG API failures). Has sales-engineering experience supporting enterprise renewals, including a million-dollar contract renewal while at Siemens working with Ford stakeholders.”