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Vetted Pinecone Professionals
Pre-screened and vetted.
MARCUS JOHNSON
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
Senior Full-Stack Python Developer specializing in cloud-native RAG and microservices
Mid-level AI/ML Engineer specializing in NLP/LLMs and production ML systems
Mid-level Machine Learning Engineer specializing in LLMs and RAG systems
Intern AI/ML Engineer specializing in LLM agents, RAG, and computer vision
Software Engineering Intern specializing in backend APIs, Kafka data pipelines, and cloud systems
Executive Engineering Leader specializing in FinTech payments and real-time platforms
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Intern Full-Stack Engineer specializing in AI-driven RAG applications
Mid-level AI/ML Engineer specializing in GPU-accelerated LLM and vision systems
Senior Backend Engineer specializing in scalable AWS serverless and data pipelines
Staff Software Engineer specializing in FinTech, AI/ML, and cloud microservices
Mid-Level Software Engineer specializing in distributed systems and AI agent platforms
Senior Customer Success & Technical Account Leader specializing in AI/ML infrastructure
Senior Full-Stack Engineer specializing in AI/ML, LLMs, and RAG systems
Mid-level Generative AI & Machine Learning Engineer specializing in LLMs and RAG
Senior Machine Learning Engineer specializing in LLMs and Generative AI
Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms
Venu Dave
Junior Software Development Engineer specializing in backend data platforms and LLM applications
“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”
Rajan Souda
Mid-level AI Engineer specializing in Generative AI and MLOps
“Built and deployed a production LLM-powered clinical support assistant at BJC HealthCare (RAG + transformer) to answer patient questions, summarize clinical notes, and support appointment workflows. Implemented PHI-safe data pipelines (Spark/Hadoop/Kafka) with automated scrubbing, dataset versioning, and audit logs, and runs the system on Docker/Kubernetes with Pinecone vector search while partnering closely with clinical operations staff.”
Jeremiah Medina
Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps
“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”