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Vetted AI & Machine Learning Professionals in California
Pre-screened and vetted in California.
Popular Titles
Mid-Level Software Engineer specializing in Data, ML, and LLM systems
Mid-level Applied Machine Learning Engineer specializing in multimodal healthcare AI
Intern AI/ML Engineer and Full-Stack Developer specializing in computer vision and cloud systems
Mid-level Applied AI Developer specializing in Generative AI and Python
Mid-level Machine Learning Engineer specializing in deep learning and applied research
Mid-level AI Engineer specializing in autonomous agents and AI security
Intern AI Engineer specializing in LLMs, RAG, and graph/vector databases
Junior Full-Stack AI Systems Engineer specializing in agentic AI and RAG pipelines
Junior AI/ML Software Engineer specializing in trustworthy ML and full-stack APIs
Senior Forward Deployed Engineer specializing in LLMs, RAG pipelines, and enterprise AI deployments
Mid-level Machine Learning Engineer specializing in NLP, time-series forecasting, and edge AI
Mid-level Machine Learning Engineer specializing in healthcare risk prediction and GenAI
Mid-level Machine Learning Engineer specializing in Generative AI, NLP, and recommender systems
Mid-level Full-Stack AI Engineer specializing in agentic systems and scalable platforms
Rui Zhao
Junior Machine Learning Engineer specializing in semantic search and retrieval systems
“Built and shipped a production RAG system (“TROJAN KNOWLEDGE”) for answering questions over technical PDFs, using a 3-stage retrieval stack (BM25 + FAISS + cross-encoder) to lift F1 from 71% to 84%. Drove major performance gains with a 3-level cache (memory/Redis/disk) cutting latency from ~200ms to ~10ms, and added Prometheus/Grafana monitoring plus LangChain-based fallback logic to handle OpenAI rate limits under load.”
Rakesh Deshalli Ravi
Mid-level Data Science & AI Engineer specializing in LLMs and cloud ML platforms
“Built and deployed an LLM-powered mental health therapy assistant at AppHealth that segments users by stress level and delivers personalized, non-medical guidance. Implemented healthcare-focused safety guardrails (secondary LLM output filtering) and a multi-agent router workflow validated via statistical tests and therapist review, then scaled training/inference on AWS (EC2/Lambda/DynamoDB) with Kubernetes.”
Yashi Agarwal
Mid-level Machine Learning Engineer specializing in NLP, Generative AI, and RAG systems
“Built and deployed a production LLM-powered phone assistant for a healthcare clinic, combining streaming STT/TTS with RAG over approved clinic documents and strict safety guardrails to prevent unverified medical advice, plus seamless human handoff. Also has hands-on Apache Airflow experience building robust daily ML/data pipelines with data validation, retries/timeouts, monitoring, and metric-gated model deployment, and iterates closely with clinic staff using real call reviews.”
Yogita Adari
Mid-level AI Engineer specializing in generative AI, multimodal evaluation, and agentic RAG systems
“Built and productionized an agentic LLM automation system for an insurance client to determine medication eligibility, using prompt-chaining plus a RAG pipeline over policy rules and deploying on AWS (Lambda/Step Functions, Bedrock) with a serverless architecture. Addressed major data/schema mismatch issues via a semantic matching pipeline and validated performance through human agreement scoring, A/B testing, KPI monitoring, and confidence-based human-in-the-loop review.”