Vetted NumPy Professionals

“FAU-based analytics candidate with hands-on academic project experience across SQL data preparation, Python/NLP sentiment analysis, and predictive modeling. They stand out for turning messy datasets into clean reporting tables, building reproducible analysis workflows, and translating findings into practical recommendations around operations, credit risk, and marketing ROI.”

“Recent graduate who independently built scholar.ai from scratch in roughly two weeks, shipping a full multimodal ingestion, retrieval, and grounded Q&A system for students. Also created Anchor SDK, an open-source framework for runtime hallucination detection and recovery, showing unusually strong depth in production LLM systems, evals, and reliability for an early-career candidate.”

“Full-stack engineer and Scrum Master who led a major monolith-to-microservices migration, including a micro-frontend Angular architecture using Native Federation and staged integration into the legacy app. Also built a React + TypeScript “Business Risk” product featuring a metadata-driven dynamic dashboard/forms layer backed by Spring Boot + GraphQL, with strong QA practices (unit/integration/E2E via Cypress), CI/CD, and feature toggles.”

“QA/supplier-performance focused candidate who uses defect and delivery data to spot recurring issues early, identify root causes tied to rushed timelines/high workload, and implement practical process changes (e.g., added validation steps and tightened defect definitions). Emphasizes clear, metric-backed communication to align internal stakeholders and suppliers, then monitors post-change results to confirm sustained improvement.”

Divya Patel

Screened

Mid-Level Software Engineer specializing in .NET and CMS platforms

Fremont, CA6y exp

“Built and owned end-to-end systems for the Department of Water Resources and NAHC, including a debt infrastructure management system and a TypeScript/React + .NET 6 CMS. Strong in shipping quickly with quality (CI/CD, automated testing), optimizing SQL Server performance for large datasets, and implementing microservices-style async processing with reliability patterns (retries/idempotency/monitoring). Also delivered widely adopted internal workflow automation and reporting using Power Automate and Power BI.”

“Built and deployed an LLM-powered automation pipeline that ingests voice and documents, transcribes/extracts key information into structured data, and routes it through backend workflows using Python/FastAPI. Uses n8n to orchestrate multi-step AI processes with validation, retries, and monitoring, and iterates with stakeholders via rapid demos to refine changing requirements.”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”

Rasheed Samady

Screened

Entry-level AI Engineer specializing in automation and ML platforms

San Francisco, CA0y exp

“Built a production Python lead intelligence pipeline that combined external APIs, website crawling, and automated opportunity brief generation, with strong emphasis on reliability, observability, and recovery. Also has hands-on Playwright experience hardening flaky, dynamic web automations and reducing intermittent failures to under 5% through logging, screenshots, session management, and retry strategies.”

“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”