Vetted Data Science Professionals

“Fintech-focused mobile engineer who built and shipped a mobile wallet to both iOS and Android app stores, implementing biometric login and AI-driven KYC (face + ID verification). Demonstrates strong customer feedback loops and production problem-solving, including resolving iOS version-specific third-party AI integration issues and improving payment UX by moving from synchronous to asynchronous processing.”

Sree Manasa Vuppu

Screened

Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG

Charlotte, NC5y exp

“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”

Pranav Mishra

Screened

Junior Machine Learning Engineer specializing in LLM agents, RAG, and MLOps

Charlotte, NC2y exp

“AI/ML engineer who has shipped production systems across computer vision and conversational agents: built a YOLOv8-based wheel fitment pipeline at a Techstars-backed automotive startup, focusing on sub-second latency, monitoring, and robust fallback mechanisms that drove 2–3x page view growth and +5–6k users. Also built a voice-based interview platform orchestrating Deepgram + GPT-4 Mini + OpenAI TTS with FSM-driven reliability, and has hands-on RAG experience (LangChain, hybrid retrieval, cross-encoder reranking, custom pseudo-query generation).”

MUNI CHARAN SINGAMALA

Screened

Mid-level Data Analyst/Data Engineer specializing in SQL, ETL pipelines, and BI dashboards

Florida, USA4y exp

“Built and supported a production analytics backend (Python, PostgreSQL/Teradata, Airflow) powering KPI/reporting dashboards, and resolved peak-time latency/timeouts through systematic SQL tuning (EXPLAIN ANALYZE, indexing, query rewrites, pre-aggregations). Also shipped an applied AI-style feature that generates plain-language report summaries from pre-computed metrics with validation, monitoring, and fallback to manual review.”

Gomathy Selvamuthiah

Screened

Junior Data/AI Engineer specializing in MLOps, real-time pipelines, and LLM applications

Portland, US2y exp

“Built an LLM-driven MLOps agent at SBD Technologies that automated an EV-charging prediction workflow end-to-end, integrating with real-time Kafka/FastAPI systems supporting 120K+ chargers at 99.99% event delivery. Addressed frequent schema drift by implementing SQLAlchemy/Flyway validation (60% reduction in drift issues) and deployed as Kubernetes microservices with GitHub Actions CI/CD; also has Airflow-based ingestion/crawling experience into Snowflake and stakeholder-facing delivery via a Fleetcharge PWA.”

“Built and owned a production RAG-based internal knowledge assistant end-to-end, from experimentation through cloud deployment and monitoring. Demonstrated strong practical GenAI judgment by choosing prompt optimization and retrieval tuning over fine-tuning for dynamic data, driving a 40% to 50% reduction in time to answer while improving relevance, lowering hallucinations, and increasing productivity.”

Narayan Anantha Krishnan

Screened

Junior AI/ML Engineer specializing in LLMs, RAG, and cybersecurity

Syracuse, NY2y exp

“AI/full-stack builder with hands-on experience shipping conversational and agentic products, including a travel itinerary assistant, a multi-agent data analysis platform, and a self-correcting RAG system. Also brings academic research depth from Syracuse University, where they helped develop tiny-LLM-based IoT threat mitigation and presented an accepted paper at FLAIRS 39.”

“F2P mobile LiveOps/product specialist (iOS) who acted as a bridge between product, design, and data during the live phase—analyzing player behavior, identifying loop friction, and iterating on progression, rewards, and live events. Emphasizes trust-preserving monetization through incremental cohort rollouts and tight monitoring of retention, funnel, revenue, and player feedback signals.”

“Backend engineer at PlatePost who built an AI-driven food pairing/recommendation feature for restaurants using Google Gemini, shipping quickly by caching results with a 24-hour refresh and manual override. Emphasizes practical reliability/security patterns (logging, error handling, tenant-scoped queries) and proactively caught an accessibility issue via screen reader testing.”

Riya Stanly

Screened

Intern Data Scientist specializing in machine learning, NLP, and LLM fine-tuning

2y exp

“Built a production-style AI meeting summarization and action-item extraction system (Azure Speech-to-Text + transformer summarization/NER) exposed via a Flask REST API, with explicit guardrails to prevent hallucinated tasks. Strong focus on reliability: modular agent/workflow design, precision-first evaluation with human-validated golden notes, and practical orchestration patterns (tool-augmented agents; ready to scale into Airflow/LangGraph/Prefect).”

“AI/ML engineer with 9+ years of experience building production recommendation and LLM systems end-to-end, from experimentation through deployment, monitoring, and retraining. Stands out for combining strong MLOps discipline with practical GenAI/RAG implementation, including measurable impact such as ~25% higher engagement on an e-commerce recommender and nearly 30% faster knowledge retrieval from internal documents.”

“Early-career candidate with academic data science and machine learning project experience, including a YouTube comment sentiment analysis project comparing LSTM and GRU models. Demonstrates a collaborative working style, structured task planning, and careful review of final deliverables in team-based project settings.”

Tony Monckton

Screened

Senior Unity VR/AR Programmer specializing in Meta Quest and real-time 3D graphics

London, UK12y exp

“Unity/VR developer who shipped a Meta Quest 2 immersive 360 training experience for Staffordshire Police as a solo programmer, including biometric gaze/reaction tracking and real-time data capture to an HTTP endpoint. Also building a Tomb Raider-like sci-fi adventure demo (Nexus 7) featuring FSM-driven character logic, motion-capture animation, custom controller optimization, and spline-following AI movement.”