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Vetted Machine Learning Engineers
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
Mid-Level Machine Learning Engineer specializing in neuromorphic perception and distributed systems
Senior AI/ML engineering leader specializing in healthcare and life sciences
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 Machine Learning Engineer specializing in NLP, recommender systems, and MLOps
Mid-level AI/ML Engineer specializing in NLP, speech AI, and RAG systems
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
Senior AI/ML Engineer specializing in GenAI, MLOps, and healthcare analytics
Senior AI/ML Engineer specializing in Generative AI and Computer Vision
Mid-level Machine Learning Engineer specializing in LLMs, multimodal AI, and backend systems
Mid-level AI/ML Engineer specializing in forecasting, MLOps, and generative AI
Principal Data Scientist specializing in LLMs, RAG, and enterprise AI products
Senior AI/ML Engineer specializing in LLMs and enterprise conversational AI
keerthana medaveni
Mid-Level AI/ML Software Engineer specializing in agentic LLM systems
“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”
Jingyi Tian
Junior Machine Learning Engineer specializing in MLOps and LLM/RAG systems
“LLM/agentic workflow builder focused on productionizing document-processing systems. Redesigned pipelines with LangGraph + RAG, schema-aware validation, and eval/monitoring loops; known for fast incident diagnosis (restored accuracy from ~70% to >95% same day). Partners closely with sales and stakeholders to deliver tailored demos and drive adoption (reported +40%).”
“LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.”