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Vetted AI & Machine Learning Professionals in the Bay Area
Pre-screened and vetted in the Bay Area.
Popular Titles
Mid-level Machine Learning Engineer specializing in computer vision and LLM systems
Junior Software Engineer specializing in backend platforms and automation
Mid-level AI/ML Engineer specializing in LLM agentic systems and MLOps
Senior Machine Learning Engineer specializing in computer vision and edge AI
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Intern Software Engineer specializing in GenAI and backend systems
Intern AI/Software Engineer specializing in LLM agents and full-stack automation
Mid-level AI/ML Engineer specializing in NLP, RAG, and agentic AI
Max Matkovski
Junior Machine Learning Engineer specializing in data pipelines and applied AI
“Built a production AI agent for phishing fraud detection using n8n orchestration, Claude (Sonnet 4/MCP), VirusTotal, and JavaScript formatting to generate and deliver email-based reports via Gmail. Has experience evaluating detection accuracy against known examples, iterating via feedback, and presenting AI solutions to non-technical teams.”
Alp Komban
Junior Machine Learning Engineer specializing in computer vision for medical imaging
“Applied ML/LLM practitioner working in healthcare-facing products, using RAG and LoRA fine-tuning on medical data and implementing production monitoring (confidence scoring) for clinician oversight. Has hands-on experience debugging agentic/LLM pipelines (including OCR preprocessing fixes) and regularly delivers technical demos to doctors, investors, and conferences—contributing to adoption and even helping close a funding round through end-to-end pipeline walkthroughs.”
Staff Machine Learning Engineer specializing in LLM agents and ML systems
Intern AI/ML Engineer specializing in data science, NLP, and reinforcement learning
Senior Python Backend Engineer specializing in Django, APIs, and AI automation
Intern Machine Learning Engineer specializing in LLMs, retrieval, and vision-language models
Mid-level Software Engineer specializing in AI, data engineering, and cloud systems
Director-level AI/ML engineering leader specializing in platform and product development
Raja Gurugubelli
Mid-level GenAI Engineer specializing in production RAG and LLM fine-tuning
“LLM engineer who built a production seller-support RAG system at eBay using hybrid retrieval (BM25 + Pinecone vectors) with Cohere reranking, LangGraph orchestration, and citation-grounded answers. Strong focus on reliability: semantic/structure-aware chunking, automated Ragas-based evaluation with nightly regressions, and production observability (LangSmith) plus drift monitoring (Arize). Also implemented a multi-agent fraud pipeline with AutoGen using JSON-schema contracts and explicit termination conditions.”
Aashna Kunkolienker
Junior AI Engineer specializing in agentic workflows and ML platforms
“Building a production LLM/agent system for a leading US dental provider that extracts rules from payer handbooks/portals and EDI 271 responses to validate and improve patient cost estimates. Combines GCP stack (BigQuery, GKE, Cloud Run, Pub/Sub, Vertex AI) with strong agent reliability practices (observability, validator agents, grounding, PII/hallucination guardrails, confidence scoring) and has led non-technical customer stakeholders on enterprise ServiceNow↔Aha sync and AI-powered enterprise search/summarization.”
Yashkumar Prajapati
Mid-level AI/ML Engineer specializing in SaaS analytics and production ML pipelines
“Amplitude contractor focused on AI/ML product development and backend systems, with hands-on experience shipping and improving LangChain-based event classification workflows in production. They combine LLM pipeline design, AWS data infrastructure, and pragmatic human-in-the-loop controls to make analytics systems faster, more reliable, and scalable.”
Sai Dev
Mid-level AI/ML Engineer specializing in MLOps, computer vision, and NLP
“GenAI/ML engineer from Lucid Motors who built and productionized an LLM-powered RAG diagnostic assistant for manufacturing and maintenance teams, deployed on AWS with Docker/Kubernetes and MLflow. Demonstrates end-to-end ownership from retrieval/prompt design to scalability, monitoring, and workflow integration via APIs, plus production ML pipeline orchestration with Kubeflow (Spark/Kafka + TensorFlow) for predictive maintenance use cases.”