Vetted Apache Spark Professionals

Tamanna Nandlal Choithani

Screened

Entry-level Full-Stack Engineer specializing in AI and distributed systems

California, USA1y exp

“Full-stack engineer who built an AI-based inventory/procurement query system at Botlily/Botlerly using Flask and Google Sheets as a live knowledge base, overcoming Sheets latency with caching and structured in-memory models. Demonstrated strong LLM product engineering (40% accuracy improvement via preprocessing/prompting) and customer-driven iteration with bar/restaurant owners, evolving the tool into a more comprehensive inventory management and forecasting solution.”

“Engineer with hands-on experience building adaptive assessment and LMS-style platforms across React/TypeScript, edge/serverless backends, and Postgres, with strong evidence of cross-layer debugging and performance optimization. Also brings ML product experience from a small-team internship, where they shipped a CatBoost-powered investor demo under ambiguity and created reusable inference infrastructure.”

“Full-stack product engineer who led system design and backend/cloud architecture for a senior-living platform spanning an Android kiosk and admin web portal. They combine Azure microservices expertise with strong accessibility instincts, and their UI/UX improvements for seniors and wheelchair users reportedly helped drive 21% revenue growth and a new customer through word of mouth.”

RAUNAQ BEDI

Screened

Entry-level Software Engineer specializing in AI, data engineering, and cloud DevOps

San Francisco, CA1y exp

“Product-minded full-stack engineer with strong React/TypeScript, serverless AWS, and Postgres depth, highlighted by owning real-time personalization and onboarding experiences at mParticle. Stands out for combining deep performance debugging with measurable product impact—improving activation by 28%, reducing time-to-insights by 35%, and building reusable internal platform primitives adopted by 12 teams.”

vinod yendluri

Screened

Mid-level MLOps Engineer specializing in production machine learning systems

Hyderabad, India3y exp

“Built an end-to-end churn prediction platform at Freddi's Flowers spanning Spark ETL on AWS, model serving, monitoring, and a stakeholder-facing dashboard. Stands out for combining MLOps rigor with product thinking—adding explainability, action-oriented workflows, and config-driven multi-tenant architecture while improving latency and automating drift response.”

“Pre-seed startup cofounder with hands-on experience in federal contracting through the Apex accelerator, including six competitive bids and direct involvement in pitch prep and investor readiness. Brings an unusual mix of AI opportunity scoping, deep-tech/patent exposure, and nonprofit ecosystem-building, with a clear ability to translate technical work into investor and partner value.”