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Vetted FAISS Professionals
Pre-screened and vetted.
Staff Machine Learning Engineer specializing in LLM agents and ML systems
Mid-level Backend/Platform Engineer specializing in distributed systems and data platforms
Mid-level Machine Learning Engineer specializing in MLOps and applied AI
Senior Software Engineer specializing in backend microservices and AI/ML integrations
Junior ML Engineer specializing in GenAI agents, RAG, and computer vision
Mid-level GenAI & Analytics Engineer specializing in LLM and cloud cost/finance analytics
Mid-level Machine Learning & Generative AI Engineer specializing in enterprise RAG and MLOps
Mid-level AI/ML Engineer specializing in NLP, MLOps, and compliance-focused ML systems
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and document intelligence
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services
Mid-level AI/ML Engineer specializing in NLP, MLOps, and financial risk & fraud analytics
Mid-level AI Engineer specializing in Generative AI and LLM/RAG systems
Senior Data Scientist specializing in LLMs, NLP, and anomaly detection
Mid-level Software Engineer specializing in AI, data engineering, and cloud systems
Intern AI/Backend Engineer specializing in LLM agents and cloud microservices
Mid-Level Software Engineer specializing in AI systems and full-stack development
Mid-level AI/ML Engineer specializing in forecasting, MLOps, and generative AI
silin liu
Mid-level AI/ML Engineer specializing in LLM agents, RAG, and enterprise ML systems
“Built a production multi-agent recommendation/RAG system for internal data analysts to speed up weekly report creation by improving document discovery and automating report/SQL generation. Implemented LangGraph-based orchestration with deterministic agent routing, robust error handling (interrupt/resume), and metadata-driven semantic chunking for diverse PDF/document formats, plus monitoring for latency, throughput, and token/cost efficiency.”