Vetted MLOps Professionals

Rupak Chand

Screened

Junior ML Data Associate specializing in AI training data and LLM prompt evaluation

Connecticut2y exp

“Applied ML/embodied AI practitioner who built an on-device gesture-control system for smart-home lights using Raspberry Pi + camera, focusing on privacy-preserving real-time inference and hardware-constrained optimization (async pipeline + TF Lite INT8). Also made a high-impact architecture decision for an ML content evaluation/QA pipeline processing millions of annotated text samples weekly, reducing batch runtime from ~6 hours to ~40 minutes while lowering compute cost.”

Sai Rahul Dasari

Screened

Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems

USA3y exp

“Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.”

“Platform/infra engineer with deep Kubernetes (EKS) and VMware vSphere experience who has led a monolith-to-microservices transition for a credit lending decision platform. Built GitOps-driven Terraform delivery with strong governance, and used LaunchDarkly-based progressive rollouts plus Datadog observability to safely ship multiple times per day (reported ~6x throughput and 1/3 the bugfix tickets vs legacy). Also operates hybrid on-prem/AWS networking (firewall + Transit Gateway, BGP) and has handled high-stakes datacenter migrations (100TB Storage vMotion) under Sev1 conditions.”

Shashank R

Screened

Senior Data Engineer specializing in cloud data platforms and real-time analytics

Las Vegas, NV6y exp

“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”

“Analytics professional with Intuit experience spanning modern data stack work, behavioral segmentation, and applied AI. They built dbt/Snowflake pipelines powering retention and churn dashboards, automated feedback classification with OpenAI/LangChain, and partnered closely with product and marketing teams to turn analytics into onboarding, targeting, and lifecycle messaging decisions.”

“ML/AI engineer with hands-on experience building production MLOps systems for predictive maintenance and demand forecasting, including deployment, monitoring, and iterative retraining. Also shipped a RAG-based employee onboarding chatbot integrated with ServiceNow APIs and reports business impact of roughly $300k/month in reduced stockout and overstock costs.”

“Built from scratch a social media analytics MVP featuring an LLM-powered semantic search agent that became a core part of the product experience within a 6-week deadline. Stands out for focusing on production readiness early—retrieval-first design, explicit tool constraints, structured outputs, idempotent services, and practical eval/monitoring loops rather than demo-only AI.”

“Graduate student who has built both full-stack web products and an offline Android AI assistant for visually impaired users. Particularly interesting for roles spanning product engineering and applied AI, with hands-on experience in on-device ML, privacy-sensitive deployment, and making complex AI interactions usable for non-technical users.”

“Built and shipped enterprise AI products including a conversational SQL analytics platform and a production RAG system at Johnson & Johnson. Combines full-stack engineering with LLM systems expertise, and has delivered measurable impact at scale, including 48% lower retrieval latency and 37% better response relevance across 12M+ records.”

Saipraneeth Ketireddi

Screened

Mid-level AI/ML Engineer specializing in LLM automation and healthcare analytics

Dallas, TX4y exp

“Full-stack AI engineer who has repeatedly taken ambiguous automation and agentic products from prototype to production, including a BRD automation platform that cut manual processing by 70% and a healthcare RAG assistant with long-term memory. Stands out for combining backend/AI orchestration depth with strong product instincts around trust, observability, security, and non-technical user experience.”