Vetted Machine Learning Professionals

“Full-stack engineer with hands-on experience spanning real-time AI products, large-scale payments migration, internal research infrastructure, and open-source ML tooling. Particularly compelling is the mix of low-latency React/Node/TypeScript systems work, zero-downtime migration of 50,000 accounts across 12 regions, and proactive contributions to Kubeflow build and security reliability.”

Sreenaina Koujala

Screened ReferencesStrong rec.

Mid-level Full-Stack & AI Engineer specializing in cloud and intelligent systems

Ashburn, VA8y exp

“Builder with experience across government contracting, engineering automation, and solo AI product development. They architected a serverless AWS pipeline that converted unstructured BIM data into IFC 3D models, built an enterprise internal-data chatbot with auditability and guardrails at Steampunk, and independently launched an AI study platform using Claude. Strong fit for early-stage or ambiguous environments where end-to-end ownership and practical AI systems matter.”

“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”

Keith Aumiller

Screened

Director-level Data & AI Leader specializing in enterprise transformation

Philadelphia, PA22y exp

“Built Cigna Health’s risk-based management/monitoring system used as a primary product for pharmaceutical clients, supporting clinical trials and utilized during the COVID-19 pandemic. Currently running a community-based startup (details kept proprietary) and is open to executive roles or joining a strong team with a clear path to success, evaluating opportunities via ROI.”

“Recent Cornell graduate with roughly 18 months of unusually high-impact Solutions Engineering experience, already owning enterprise AI engagements for Citi and Samsung at WorldLink US. Stands out for combining technical pre-sales with hands-on prototyping and delivery, including local on-device AI for Samsung QA and helping take an AI security product from architecture to first $100K close.”

“Senior product leader with experience spanning luxury e-commerce and consumer education, including leading personalization and AI-driven shopping experiences at The RealReal and serving as Chief Product Officer/strategic product consultant at OMGYES. Stands out for combining ML-powered product strategy, strong UX judgment, and cross-functional leadership to deliver measurable business impact, including conversion and revenue gains at scale.”

“Enterprise CSM with experience at IBM and Cloudera, focused on AI and cloud modernization engagements. Drives adoption, renewals, and expansion by building success plans with measurable ROI/usage outcomes, mediating complex stakeholder priorities, and unblocking deployments through tight Product/Engineering/Sales coordination. Also brings strong GTM analytics capability (Salesforce/HubSpot/GA/Tableau/SQL) to improve funnel performance and pipeline conversion.”

“Startup-focused technology leader who has supported two startups over ~10 years, including conducting initial M&A/technology-fit research and serving as CTO to build required platforms. Recently automated manual marketing lead processing with agentic AI and drove workflow standardization through user interviews to align teams on a common process.”

“Early-stage investing/venture sourcing profile with experience building a structured founder-sourcing pipeline across online communities, universities/hackathons, and in-person events. Interned at OrCap LLC, where they converted cold outreach into qualified founder conversations by staying useful over time (insights, relevant intros) and running structured first calls that led to internal greenlights for deeper diligence.”

Samuel Ehrenstein

Screened

Mid-level Computer Vision & ML Researcher specializing in medical imaging and 3D vision

Chapel Hill, NC4y exp

“PhD (CS) candidate with hands-on autonomy and robotics experience: improved safety-critical behavior for Kodiak’s self-driving 18-wheeler trucks, increasing overtaking clearance by ~2 feet and reducing safety alerts. Also debugged a C++ SLAM system for 3D colon reconstruction and built a low-budget distributed simulation cluster using Linux, Docker, and Python, plus implemented multi-hop SSH-based comms for an underwater robotics competition minibot.”

“Zero Trust security product lead focused on UI/API delivery, stability, and customer adoption at enterprise scale, including deployments serving 1200 customers. Stands out for hands-on production debugging across the full stack, customer-facing incident ownership, and a pragmatic approach to turning failures into automated regression coverage.”

“Built and owned an end-to-end agentic RAG chatbot platform for Baptist Health that helped clinicians access policy and clinical documents faster, reducing manual lookup by 80% and delivering about $2M in annual savings. Brings strong healthcare GenAI production experience, including HIPAA-aligned governance, PHI redaction, observability, evaluation, and scalable Python/Kubernetes deployment practices.”

“At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.”

“Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.”

“AI engineer building and deploying deep-learning-based optimization/control systems for petrochemical plants, with a focus on maintaining operational stability under real-world constraints. Core contributor to model and inference design; introduced a stability-focused non-linear objective and sped up second-layer optimization via on-the-fly first-order approximations. Experienced using Kubernetes for end-to-end testing and effective in translating customer expectations into measurable evaluation plots for non-technical stakeholders.”

“Built a production AI agent for phishing fraud detection using n8n orchestration, Claude (Sonnet 4/MCP), VirusTotal, and JavaScript formatting to generate and deliver email-based reports via Gmail. Has experience evaluating detection accuracy against known examples, iterating via feedback, and presenting AI solutions to non-technical teams.”

“ML/LLM practitioner with experience at Truveta building an LLM-based evaluation framework; identified non-overlapping evaluator failure modes and proposed an ensemble approach that enabled scaling training data and drove ~5% performance gains across multiple internal projects. Strong focus on robustness to distribution shift (augmentation/domain adaptation/meta-learning) and production reliability via monitoring, drift detection, and safe fallbacks.”

Richard Adams

Screened

Executive Technology Leader (CEO/CTO) specializing in IoT, wireless audio, and connected devices

Los Angeles, California24y exp

“Repeat entrepreneur with multiple exits who emphasizes rigorous pre-build market research and customer discovery to validate product-market fit. Previously built Hygiene IQ for restaurant/hospitality markets and describes an end-to-end process from prototyping and MVP testing through supply chain. Currently has a pitch deck for an AI-enabled holistic companion for healthy aging (physical, mental, emotional, and social wellbeing).”

Syed Daim Ali

Screened

Intern Software Engineer specializing in FinTech and AI platforms

Sunnyvale, CA0y exp

“Systems-focused engineer who built an OS kernel with multithreading, priority scheduling, system calls, and synchronization primitives, and debugged race conditions end-to-end. While not yet hands-on with ROS/SLAM, they clearly connect low-level concurrency and scheduling decisions to deterministic, reliable robotics-style real-time workloads.”

“Graduate robotics researcher (Georgia Tech/Georgia Tech Research Institute) who helped modernize the Georgia Tech Robotarium by migrating its comms stack from MQTT to ROS2 across MATLAB/Python and updating embedded Teensy firmware for new sensors. Currently validating ToF distance sensors and integrating IMUs, with planned GTSAM factor-graph SLAM sensor fusion; also debugged and improved a decentralized coverage-control algorithm at swarm scale (1000–2000 agents) using computational geometry and literature-backed methods.”

“Industrial AI/ML practitioner with experience deploying real-time monitoring and anomaly detection in a regulated Sanofi vaccine manufacturing facility, including root-cause workflows, logging/alerting, and SOP-aligned validation—achieving ~90% faster anomaly detection. Also built Python/NLP-style automation to accelerate instrumentation & control documentation (~40% faster) and delivered end-to-end predictive analytics for an agri-food operations/distribution client using close operator and leadership feedback loops.”

“Robotics software engineer who built the full control stack for a fleet of manufacturing/repair robots in Relativity Space R&D (perception, planning, motion control, integration, deployment). Has ROS/ROS 2 experience spanning custom SLAM (LiDAR+IMU), multi-robot coordination, and multi-drone control (Pixhawk 4, minimum-snap trajectories), with strong real-world debugging and simulation/CI testing practices (Gazebo, CI/CD, some Docker).”

“Backend/AI engineer at Intuit who built a production AI-powered case assistant for support agents (FastAPI on AWS EKS) combining Postgres case data, OpenSearch retrieval with embedding reranking, and internal LLMs. Improved peak-season reliability by diagnosing P95/P99 timeout spikes and cutting P95 latency from ~800ms to <400ms via composite indexing, keyset pagination, connection pool tuning, and caching, while adding grounded-generation guardrails (evidence packs, confidence thresholds, fallbacks, human-in-the-loop).”

Ho-Wei Lu

Screened

Junior Robotics Engineer specializing in motion planning and control

Berkeley, USA1y exp

“Robotics software engineer who built a ROS2-based ping-pong ball interception system on a 7-DOF Sawyer arm, spanning real-time vision, trajectory prediction, and an MPC joint-velocity controller to hit a flying ball within ~1 second. Demonstrated strong real-time debugging and systems integration skills (timestamp-based latency analysis, event-based redesign, ROS2 QoS tuning) and is currently working with Isaac Sim in Docker with GitHub-based CI/CD for assembly-task simulation.”