Pre-screened and vetted in the Greater Seattle.
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision, and LLMs
Mid-level DevOps/MLOps Engineer specializing in multi-cloud infrastructure and CI/CD
Junior Software Developer & AI Trainer specializing in LLM training and web apps
Mid-level DevOps/MLOps Engineer specializing in AWS/GCP infrastructure and Kubernetes
Junior AI/ML Engineer specializing in NLP, LLMs, and MLOps deployment
“Built and deployed NeuroDoc, a production-grade RAG system for PDF Q&A that delivers citation-backed answers with strong anti-hallucination guardrails. Experienced in orchestrating and scaling ML/LLM pipelines with Kubernetes, Airflow/Prefect, and PyTorch Distributed, and in building rigorous evaluation and citation-verification tooling to ensure reliability in production.”
Mid-level Machine Learning Engineer specializing in cloud-native generative AI for healthcare
“AI engineer at Cleveland Clinic building production LLM/NLP systems for radiology documentation, focused on HIPAA-aware, real-time performance across ~298 campuses. Re-architected infrastructure with AWS event-driven services to handle scaling and improved SLA compliance ~40%, and complements this with a personal multi-agent debate system (CrewAI) using local Llama/Mistral plus rigorous evaluation (A/B tests, red teaming, observability).”
Intern AI Engineer specializing in agentic systems, graph analytics, and applied ML
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production inference
“AI/LLM engineer who built a production resume-parsing and candidate-matching platform at Quadrant Technologies, combining agentic LangChain workflows, VLM-based document template extraction (~85% accuracy), and a hybrid RAG backend for resume-to-JD search. Notably integrated automated LLM evals and metric-based CI/CD quality gates to catch silent prompt/model regressions, and led a 3-person team across frontend/backend/testing.”
Director-level AI/ML Engineer specializing in LLMs, RAG, and MLOps