.png){kind=logo}
Vetted Recommender Systems Professionals
Pre-screened and vetted.
Principal Data Scientist specializing in Generative AI, LLMs, and ML platforms
Senior Machine Learning Engineer specializing in LLMs and Generative AI
Senior IT Project Manager and Scrum Master specializing in AI, cloud, and data transformation
Mid-level Data Scientist specializing in causal inference and data engineering
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and real-time ML systems
Intern Machine Learning Engineer specializing in recommender systems and financial risk modeling
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and MLOps
Mid-level AI Engineer specializing in LLM agents, RAG, and enterprise GenAI
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Mid-level Software Developer specializing in backend cloud and API platforms
Senior AI/ML Engineer specializing in Generative AI and cloud-native ML systems
Rubeena Riyas
Senior AI Engineer specializing in LLM agents, RAG, and scalable data platforms
“ML/data engineer who owned an end-to-end production sales analytics pipeline at 15,000+ user scale, delivering ~50% compute reduction, ~80% faster reporting, and ~$1.2M impact. Also shipped a production RAG-based AI assistant over internal BigQuery/docs with evaluation metrics and safety guardrails, and built shared Python libraries to standardize reliability and accelerate engineering teams.”
Longyang Xu
Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products
“Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.”
Megan Gwynne
Executive product leader specializing in e-commerce, marketplaces, and growth
“Senior product leader with experience spanning luxury e-commerce and consumer education, including leading personalization and AI-driven shopping experiences at The RealReal and serving as Chief Product Officer/strategic product consultant at OMGYES. Stands out for combining ML-powered product strategy, strong UX judgment, and cross-functional leadership to deliver measurable business impact, including conversion and revenue gains at scale.”
Max Matkovski
Junior Machine Learning Engineer specializing in data pipelines and applied AI
“Built a production AI agent for phishing fraud detection using n8n orchestration, Claude (Sonnet 4/MCP), VirusTotal, and JavaScript formatting to generate and deliver email-based reports via Gmail. Has experience evaluating detection accuracy against known examples, iterating via feedback, and presenting AI solutions to non-technical teams.”
Haider Shah
Principal AI/ML Architect specializing in GenAI, LLMs, RAG, and Agentic AI
“FinTech/AI engineer who has shipped an end-to-end discrepancy-detection product for financial managers using Next.js, FastAPI/GraphQL, Pinecone, and AWS (with dev/staging/prod, observability, A/B testing, and documentation). Also built an AI-native “AI Genesis” system with agentic cyclic workflows, routing, and tool use, and has experience modernizing legacy systems via the strangler fig pattern while coordinating with senior stakeholders on a 5G autonomous simulation platform.”