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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and Computer Vision
Senior Software Engineer specializing in AI, ML infrastructure, and backend systems
Mid-level Machine Learning & GenAI Engineer specializing in RAG and multimodal AI systems
Junior Data Analyst specializing in analytics, ETL, and machine learning
Mid-level AI/ML Data Engineer specializing in MLOps and Generative AI
Mid-level AI & Data Engineer specializing in cloud ML, RAG systems, and ETL automation
Mid-level Data Scientist specializing in NLP, Generative AI, and ML pipelines
Mid-level MLOps/Machine Learning Engineer specializing in cloud-native production ML
Senior Generative AI Engineer & Full-Stack Developer specializing in LLMs and microservices
Senior Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Mid-level AI Engineer specializing in agentic LLM workflows and RAG systems
Balakrishna Mylapilli
Mid-level AIML Engineer specializing in production ML and MLOps
“ML practitioner who built a production customer risk scoring system to replace slow manual approvals, owning the full pipeline from feature engineering and XGBoost training to deploying a Dockerized FastAPI prediction service. Emphasizes reliability and business-aligned evaluation (recall/ROC-AUC, threshold tuning, drift monitoring) and is comfortable translating model decisions into stakeholder metrics like conversion rate (experience at EasyBee AI).”
Habtom Desta
Mid-level Data Scientist specializing in Python, ML, and BI dashboards
“Data/NLP practitioner who builds production-oriented pipelines for unstructured text: entity extraction, topic modeling (LDA/BERTopic), and semantic search using Sentence-BERT embeddings with FAISS. Emphasizes rigorous evaluation (coherence/silhouette + manual review), entity resolution with validation, and scalable workflow orchestration using Airflow/Prefect with Spark/Dask.”
SaiDheerajReddy Gadikota
Mid-level AI Engineer specializing in agentic systems and enterprise LLM platforms
“Current AI engineer at a startup who has spent the last year architecting multi-agent systems for software development workflows. Stands out for combining LLM speed with engineering discipline—using tools like Pydantic, LangGraph, and LangChain to build reliable, production-ready agent workflows with validation, routing, and retry logic.”
“LLM/RAG engineer at Connex AI who built and deployed a production healthcare agent to extract clinical insights from medical data/notes. Strong focus on real-world reliability—hallucination mitigation (citations, schema validation, confidence thresholds, rejection logic), custom LangChain orchestration (query rewriting, fallback paths), and production evaluation/observability—while collaborating closely with clinical SMEs to ensure clinical fit and time savings.”
Mid-level Full-Stack/AI Engineer specializing in LLM microservices, RAG, and data pipelines
Mid-level Data Scientist specializing in GenAI, MLOps, and computer vision for robotics