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Vetted AI & Machine Learning Professionals
Pre-screened and vetted.
Popular Titles
Mid-level GenAI/ML Engineer specializing in LLM agents, RAG, and document intelligence
Mid-level AI/ML Engineer specializing in Generative AI agents and enterprise analytics
Intern software engineer specializing in full-stack, data engineering, and ML systems
Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics
Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI
Junior growth and research professional specializing in AI, biotech, and venture
Mid-level GenAI/ML Engineer specializing in LLMs, RAG, and agentic AI
Pavan Kalyan
Mid-level AI Engineer specializing in GenAI agents and RAG for IT operations
“Built and operates a production LLM agent for enterprise IT operations that triages and drafts resolutions for high-volume ServiceNow tickets using LangChain + RAG (Pinecone/pgvector) and AWS Bedrock/OpenAI. Emphasizes reliability with schema-validated stages, offline eval datasets from real tickets, and CloudWatch-driven monitoring/guardrails; system scales to 40K+ tickets/month and cut resolution time ~28%.”
Senior Machine Learning Engineer specializing in AI systems, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Senior Machine Learning Engineer specializing in MLOps and Generative AI
Mid-level AI/ML Developer specializing in FinTech fraud detection and GenAI assistants
Krishnapriyanka Ponnaganti
Mid-level AI/ML Engineer specializing in agentic AI and production ML systems
“ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.”
Rithindatta Gundu
Mid-level AI/ML Engineer specializing in LLM systems and cloud MLOps
“Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.”