Vetted Data Ingestion Professionals

“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”

“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”

“Data engineer with eBay experience owning end-to-end pipelines for real-time order and user behavior analytics at 10M+ records/day. Strong in PySpark/SQL transformations, Airflow reliability patterns, and production observability (CloudWatch), with measurable outcomes including improved data quality and 30–40% query performance gains. Also built Python data APIs for analytics/ML consumers with versioning and backward compatibility.”

ChinmaySanjay Kawle

Screened

Junior Software Engineer specializing in cloud developer tools and backend APIs

Seattle, WA2y exp

“Summer intern on AWS Lambda tooling team who shipped Finch support in AWS SAM CLI, adding OS/runtime detection and robust fallback behavior to preserve Docker compatibility across developer environments. Also built an end-to-end RAG system for querying arXiv quantitative finance papers using Postgres/pgvector with two-stage retrieval, citation-grounded prompting, and rigorous evaluation loops driven by IR metrics and user feedback.”

Vismay Patel

Screened

Senior AI & Machine Learning Engineer specializing in NLP, GenAI, and MLOps

Berkeley, CA7y exp

“ML/GenAI practitioner with healthcare domain depth who built and deployed a production cervical-cancer EMR classification system using a hybrid rules + medical BERT approach, optimized for high recall under severe class imbalance and PHI constraints. Experienced running end-to-end production ML/LLM pipelines with Apache Airflow (validation, promotion/rollback, monitoring, retraining) and partnering closely with clinicians to calibrate thresholds and implement human-in-the-loop review.”

“Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.”