Vetted Data Pipelines Professionals

“Entrepreneurial builder and former founding CTO of a Y Combinator startup that was acquired. Now in the planning stage for a new venture (considering edtech, media creation, and food/"intelligent servicing"), emphasizing early design partners, rapid testing, and iteration to validate ideas.”

“Player-coach engineering leader focused on scalable data security scanning and risk detection in hybrid cloud, owning architecture and core implementation of an incremental/parallel DSPM scanning engine. Shipped production improvements including 60% lower scan latency and 30% fewer false positives, with strong emphasis on correctness under concurrency, multi-tenant observability (SLOs/burn-rate alerts), and disciplined rollout practices (feature flags, shadow scans, canaries).”

Parth Vadera

Screened

Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps

Tracy, CA11y exp

“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”

Tina Bai

Screened

Executive operator-founder specializing in GTM, revenue strategy, and AI-native commercial operations

New York, NY10y exp

“Operator with Deloitte consulting experience supporting PE/VC-backed portfolio companies and current experience inside a VC-funded Series C scale-up. Building a bootstrapped D2C women’s telehealth brand (Petty Pills) with two initial SKUs, deployed tech stack, and white-labeled clinical/compliance infrastructure, leveraging AI tooling to keep operations lean while focusing on full-time operator roles.”

“Robotics student who built a fully autonomous "Pacman" robot car using ROS 2, integrating LiDAR/IMU sensing with localization, autonomous driving, and a custom RRT + A* planner. Demonstrated practical embedded optimization on an RP2040 by balancing replanning frequency with safety via rapid collision checks.”

“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”