.png){kind=logo}
Vetted Anomaly Detection Professionals
Pre-screened and vetted.
Junior Business Analyst specializing in growth analytics and experimentation
Senior growth marketing leader specializing in performance marketing and user acquisition
Senior Machine Learning Engineer specializing in LLM systems and generative AI
Mid-level AI & Machine Learning Engineer specializing in computer vision and MLOps
Mid-level AI/ML Engineer specializing in production ML, NLP, and computer vision
Senior Digital Analyst specializing in marketing analytics, personalization, and MarTech
Mid-level Java Backend Engineer specializing in Financial Services
Mid-level AI/ML Engineer specializing in NLP, Computer Vision, and Generative AI
Principal AI Platform Architect specializing in agentic AI and enterprise LLM infrastructure
Principal Machine Learning Architect specializing in AI platforms and data science
Mid-level Full-Stack Developer specializing in AI-driven FinTech platforms
Mid-level AI Data Engineer specializing in real-time streaming and LLM-powered fraud analytics
Senior Data Analyst specializing in healthcare and financial analytics
Mid-level Software Engineer specializing in distributed systems and network infrastructure
Mid-level Generative AI Engineer specializing in LLMs, NLP, and multimodal systems
Mid-Level Software Engineer specializing in backend microservices and cloud automation
Mid-level Business Analyst specializing in finance, data analytics, and AI infrastructure
Vismay Devjee
Mid-level GenAI Engineer specializing in AI agents, RAG, and LLM evaluation
“Asset Management Risk professional at Fidelity Investments who built and productionized an agentic RAG platform enabling compliance and analysts to query 10,000+ fund documents with cited answers in seconds. Implemented structure-aware semantic chunking (AWS Textract), hierarchical retrieval, and hybrid search to raise accuracy from 68% to 94%, and built an evaluation framework tracking accuracy/latency/cost/hallucinations—delivering 40+ hours/month saved and zero critical production failures.”