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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Senior AI/ML Engineer specializing in Agentic AI, RAG, and LLM systems
Mid-level AI/ML Engineer specializing in NLP, GenAI, and fraud/risk analytics
Mid-level Machine Learning Engineer specializing in Generative AI, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Mid-level Machine Learning Engineer specializing in MLOps, fraud detection, and data security
Mid-level AI/ML Engineer specializing in Generative AI agents and workflow automation
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Senior Machine Learning Software Engineer specializing in Azure enterprise AI
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG for healthcare
Junior AI Engineer specializing in distributed ML pipelines and time-series forecasting
Mid-level AI Engineer specializing in retail personalization and LLM-powered systems
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Mid-level Machine Learning Engineer specializing in production ML, MLOps, and Generative AI
Mid-level Full-Stack .NET Developer specializing in Angular, Azure, and AI integrations
Yashwanth Penugonda
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production GenAI systems
“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”
Mid-level Data Scientist & AI Engineer specializing in NLP, computer vision, and MLOps
Sravani Gangaraju
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”
Chukwuebuka Ernest-Opara
Mid-Level Full-Stack Software Engineer specializing in Cloud, DevOps, and Platform Engineering
“Backend/Node.js-focused engineer who improved a widely used shared config/logging utility library by fixing a real-world async race condition (single disk read under concurrency) and adding stronger validation/testing, resulting in more deterministic services and faster startup/build/CI times. Also builds internal platform automation spanning Python/Go/TypeScript with strong documentation practices and security-conscious customer onboarding (e.g., sensitive Kubernetes clusters, HashiCorp Vault access issues).”
Executive Technology Leader specializing in AI, edge-to-cloud platforms, and smart infrastructure
Senior Data Scientist / AI-ML Engineer specializing in LLMs, NLP, and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, Generative AI, and MLOps