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Vetted ChromaDB Professionals
Pre-screened and vetted.
Junior AI Engineer specializing in agentic LLM and RAG systems
Junior GenAI Developer specializing in RAG and LLM applications
Senior Machine Learning & AI Engineer specializing in Generative AI and MLOps
Mid-level Data Scientist specializing in ML, MLOps, and Generative AI
Intern Full-Stack Software Engineer specializing in LLM/RAG and cloud-deployed data apps
Senior AI Engineer specializing in GenAI, RAG, and enterprise platforms
Mid-level AI/ML Engineer specializing in Generative AI, multi-agent RAG, and FastAPI backends
Mid-level Machine Learning Engineer specializing in multimodal GenAI and RAG systems
Mid-level AI/ML Engineer specializing in computer vision and generative AI
Mid-level AI & Data Engineer specializing in cloud ML, RAG systems, and ETL automation
Senior GenAI Engineer specializing in agentic AI and multi-agent orchestration
Senior AI/ML Engineer specializing in Generative AI, RAG, and multimodal LLM systems
Junior Machine Learning Engineer specializing in Generative AI and MLOps
Mid-level Data Scientist / GenAI Engineer specializing in LLM agents, RAG, and OCR
Junior Full-Stack Software Engineer specializing in AI/RAG systems
Mid-level AI Engineer specializing in LLM safety, red teaming, and evaluation
Mid-level Software Engineer specializing in backend systems and AI applications
Mid-Level Software Engineer specializing in cloud microservices and AI automation
Mid-Level Software Engineer specializing in AI/ML, cloud deployment, and full-stack systems
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Mid-level ML Engineer specializing in AI systems and LLM infrastructure
Rukmini Pisipati
Junior AI/ML Engineer specializing in LLM automation and NLP
“Built and shipped a production LLM hallucination detection and monitoring pipeline using semantic-level entropy (embedding-clustered multi-generation variance) to flag unreliable outputs in downstream automation. Implemented a scalable async architecture (FastAPI + Docker + Redis/Celery) with strong observability (structured logs + PostgreSQL) and developed evaluation loops combining controlled prompts and human review; also partnered with non-technical stakeholders on AI-driven form validation/document processing.”