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Vetted Data Scientists in the Bay Area
Pre-screened and vetted in the Bay Area.
Senior Data Scientist / AI/ML Engineer specializing in NLP, LLMs, and RAG systems
Mid-level Data Scientist specializing in ML, RAG chatbots, and analytics
Mid-level AI/ML Engineer & Data Scientist specializing in MLOps, LLMs, and anomaly detection
Mid-level Data Scientist specializing in NLP, deep learning, and compliance automation
Intern AI Engineer specializing in LLMs, RAG, and graph/vector databases
Mid-level Machine Learning Engineer specializing in Generative AI, NLP, and recommender systems
Allen Saunders
Senior DevOps/Solutions Engineer specializing in CI/CD, cloud platforms, and API integrations
“Solutions Architect with 5+ years leading pre- and post-sales engagements, focused on taking complex tooling from test/prototype to secure production through a structured discovery-to-deployment approach. Experienced in LLM workflow troubleshooting using tools like Langfuse/Gopher and in developer enablement via concise, hands-on workshops (e.g., Jenkins on Kubernetes at scale). Has navigated internal and external blockers to drive adoption and keep enterprise deals moving (including a Jenkins sale to Love's).”
Amit Gangane
Junior Data Scientist specializing in agentic AI and RAG pipelines
“LLM/agentic systems builder who shipped production workflows at Angel Flight West and Eureka AI, combining LangGraph + RAG (Postgres/pgvector) with strong observability (LangSmith/Langfuse). Delivered large operational gains (address lookup cut from 10 minutes to 60 seconds; accuracy to 92%) and has a track record of quickly stabilizing customer-critical pipelines (Pydantic-enforced JSON for ETL) while partnering with sales/ops to drive adoption.”
Mid-level Machine Learning Engineer specializing in LLMs, semantic search, and distributed data pipelines
Mid-level Machine Learning Engineer specializing in LLM chatbots and RAG systems
Intern Data Scientist specializing in model compression and agentic RAG systems
Drashti Magia
Junior AI Engineer specializing in LLMs, multimodal ML, and applied machine learning
“Software engineer with a disciplined, production-minded approach to AI-driven development: uses ChatGPT, Claude, GitHub Copilot, and scoped coding agents to accelerate delivery without giving up architectural judgment. Notably applied a multi-agent workflow on ClinicOps Copilot, using agents for planning, Bedrock/RAG scaffolding, and failure testing while personally owning architecture, grounding quality, and end-to-end review.”
revanth polthi
Mid-level Data Scientist specializing in Generative AI and MLOps
“GenAI/LLM engineer with production experience at Allstate building an end-to-end document intelligence workflow for insurance operations—automating document intake, classification, and risk signal extraction. Emphasizes high-reliability design for regulated/high-stakes outputs using schema enforcement, confidence thresholds, validation rules, and human-in-the-loop routing, with metric-driven offline evaluation and production monitoring.”
Atharva Joshi
Mid-level GenAI Engineer specializing in RAG systems and AI agents
“LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.”
Varun Rao
Junior Data Scientist specializing in generative AI and RAG systems
“Data scientist at Guardian Airwaves building a RAG-powered quiz generator using Grok AI, with hands-on experience solving hard document-ingestion problems (PDFs with images/tables) via unstructured.io and LlamaIndex. Has deployed production systems on AWS EC2 and brings a pragmatic approach to agent reliability (human-in-the-loop, LLM-based eval, latency/cost metrics) while effectively translating RAG concepts to non-technical stakeholders.”
Mid-level AI Engineer specializing in Generative AI and HR Tech
Mid-level Machine Learning Engineer specializing in healthcare time-series and XAI
Mid-level Software Engineer specializing in LLM agents and distributed systems
Santhi Sampath Gamidi
Mid-level AI Engineer and Data Scientist specializing in LLM agents and RAG systems
“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and agentic automation