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Vetted R Professionals
Pre-screened and vetted.
Mid-level Data/Software Engineer specializing in healthcare and FinTech analytics
Intern AI/ML Engineer specializing in LLM agents, RAG, and computer vision
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and on-device ML
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Intern Full-Stack Engineer specializing in AI-driven RAG applications
Intern-level investment and strategy professional specializing in M&A, private equity, and e-commerce
Mid-level Business Analyst specializing in data analytics and financial systems
Executive technology leader specializing in digital transformation, payments, and AI
Mid-level Software Engineer specializing in cloud infrastructure and backend systems
Senior Full-Stack Engineer specializing in AI/ML, LLMs, and RAG systems
Intern Biomedical Data Scientist specializing in healthcare AI and LLM-based clinical NLP
Mid-level Generative AI & Machine Learning Engineer specializing in LLMs and RAG
Junior Software Engineer specializing in bioinformatics and healthcare applications
Mid-level AI Solutions Architect & Product Leader specializing in enterprise GenAI systems
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Michael Vance
Senior AI & Data Engineering Manager specializing in Appian and cloud data platforms
“Deloitte consultant who led cross-functional teams delivering a Snowflake/AWS data ingestion, warehousing, and analytics platform, with a strong track record of executive alignment and risk mitigation. Built reusable business-development accelerators (including an end-to-end Appian app and a Java integration-config tool) credited with helping secure $75M+ in contracts, and has high-confidentiality experience consulting for DoD and FDA.”
Ashish Ernest Jeldi
Senior Data Scientist specializing in LLMs, agentic AI, and MLOps
“Built and shipped a production agentic LLM tool that helps internal teams update technical product whitepapers using plain-language edit requests, with strong guardrails (citations, verification, refusal/clarify flows) to reduce hallucinations and maintain compliance. Experienced taking LLM workflows from rapid LangChain prototypes to more predictable, debuggable LangGraph agent graphs, and orchestrating end-to-end ingestion/embedding/indexing/eval/deploy pipelines with Kubeflow.”
Venu Dave
Junior Software Development Engineer specializing in backend data platforms and LLM applications
“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”
Alexander Choy
Director of AI/ML Engineering specializing in MLOps, data platforms, and 3D computer vision
“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”