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Vetted Natural Language Processing Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Software Engineer specializing in healthcare AI and cloud platforms
Junior Machine Learning Engineer specializing in fraud detection and healthcare ML
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Senior AI/ML Engineer specializing in conversational AI and enterprise LLM systems
Senior AI/ML Engineer specializing in Generative AI and cloud-native platforms
Senior Software Engineer specializing in AI/ML and customer-facing platforms
Senior Machine Learning Engineer specializing in Generative AI and NLP
Senior Full-Stack AI Engineer specializing in LLM and speech-to-text products
Executive Founder-Operator specializing in AI-native products, operations, and GTM
Mid-level Data Scientist specializing in Generative AI and LLM applications
Principal Data Scientist specializing in Generative AI and security analytics
Senior Full-Stack Software Engineer specializing in AI/ML for FinTech & E-commerce
Staff ML Platform Engineer specializing in distributed training and inference
Senior AI/ML Engineer specializing in generative AI and recommendation systems
Tolulope Akinlabi
Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk
“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”
Andrew Stewart
Senior Software Engineer specializing in Healthcare AI and FinTech platforms
“Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.”