Vetted Apache Hadoop Professionals

“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”

Krishna Reddy

Screened

Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants

New York, NY6y exp

“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”

UDAY JARAJAPU

Screened

Executive engineering leader specializing in AI-native products and large-scale platforms

Fremont, CA22y exp

“Experienced cross-functional operator with background in AI, edtech, consumer mobile, cloud, and real estate search, including roles at Apple, AWS, and Trulia. Currently building Typerighter, an AI-native writing workspace focused on compliance, authenticity, and human-verifiable content, with a nuanced understanding of institutional requirements and startup/accelerator dynamics.”

“Recent internship project at Google Workspace building an LLM-driven Python backend pipeline to extract/enrich NLP features from messy customer web domains and integrate them into a Domain Feature Store for personalization and promotions. Also has hands-on Kubernetes/Docker deployment experience for a Digital Signage SaaS backend with GitHub Actions CI, plus strong streaming-systems knowledge (Kafka exactly-once, schema evolution, Flink scaling) and built an information retrieval system handling 30,000+ cases.”

“Senior technology and venture-oriented leader pursuing a CTO role, with hands-on experience advising an AI startup and a VC firm while also building incubation and technology advisory functions at Iron Mountain. Notably brought a cybersecurity product to market in six months and helped position a blockchain product through early deal development, showing a strong blend of product, strategy, and venture-building capability.”

“ML/AI engineer with hands-on ownership of production computer vision and GenAI systems, spanning real-time public safety video analytics and RAG-based knowledge assistants. Stands out for translating research-oriented approaches into scalable, monitored production systems with clear business impact, including 50% latency reductions, 25% faster response times, and 40% lower document search time.”

Kunj Amrutbhai Patel

Screened

Mid-level Software Engineer specializing in distributed backend systems on AWS

Seattle, WA4y exp

“Built production systems in the AWS ecosystem, including an internal AI assistant for diagnosing account transfer and permissions issues and an end-to-end account transfer workflow used by enterprise customers. Stands out for combining LLM/RAG design with strong distributed systems reliability practices, emphasizing guardrails, fallbacks, and operational trust in high-stakes workflows.”