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Vetted MLOps Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Senior AI/ML Engineer specializing in Computer Vision, NLP, and Generative AI
Senior Performance & GPU Virtualization Engineer specializing in AI/ML and cloud certification
Principal Data Scientist specializing in Generative AI and MLOps
Senior Machine Learning Engineer specializing in GenAI, NLP, and MLOps
Junior AI/ML Engineer specializing in NLP, LLM evaluation, and Azure MLOps
Executive Finance & Operations Leader specializing in high-growth SaaS and FinTech
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Mid-level AI/ML Engineer specializing in multimodal and generative AI at scale
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Director of Product specializing in AI-powered data platforms for connected vehicles and MLOps
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
Mid-level Software Development Engineer specializing in backend systems and ML platforms
Peeyush Dyavarashetty
Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems
“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”
Surya Singh
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”