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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving
Senior AI Engineer specializing in LLMs, RAG, and production ML systems
Executive AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Senior AI/ML Engineer specializing in LLMs, recommendation systems, and ML platforms
Staff Machine Learning Scientist specializing in NLP, LLMs, and Generative AI
Jesse Olson
Executive AI technology leader specializing in agentic AI and enterprise transformation
“Candidate is exploring a startup in the autonomous agentic AI space and is approaching it with a disciplined founder mindset. They are evaluating market opportunity, competition, customer pain, ROI, technical feasibility, and MVP options while already speaking with potential customers across verticals to validate needs and buying processes.”
Sudheer Bommichetty
Mid-level Machine Learning Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”
Staff AI Full-Stack Engineer specializing in LLMs, multi-agent systems, and Voice AI
Staff ML Platform Engineer specializing in distributed training and inference
Mid-level AI/ML Engineer specializing in Generative AI and multilingual NLP
Deepak Guntreddi
Mid-level Full-Stack Developer specializing in Java/Spring Boot and React
“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”
jagadeshwar nomula
Executive Technology Leader (CTO) specializing in AI, Search, Cloud, and Edge computing
“Founder building an enterprise agentic AI startup who has already raised about $100K (friends & family plus self-funding). Has prior and current experience engaging VCs (including outreach to both large and small firms) and emphasizes demo-driven pitching, enterprise customer validation, and targeting billion-dollar market opportunities.”
Pranav Rastogi
Director-level Product & Platform Leader specializing in AI, developer platforms, and enterprise SaaS
“Operator-turned-aspiring founder with experience building CI, cloud, and AI businesses at Harness, including P&L ownership and 0-to-1 execution. Exploring an AI-native infrastructure/control-plane thesis focused on moving enterprise workflows from AI assistance to execution, with a strong emphasis on ROI, coordination gaps, and durable moats.”
Executive Technology & Data Leader specializing in AI, cloud modernization, and digital strategy
Executive AI/IoT Engineering Leader specializing in full-stack and edge AI systems
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Machine Learning Engineer specializing in LLMs and scalable MLOps
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps