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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in MLOps, real-time ML, and LLM/RAG systems
Senior Full-Stack Engineer specializing in AI, cloud platforms, and enterprise systems
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
Mid-level Machine Learning Engineer specializing in fraud prevention and LLM systems
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Principal Data Scientist specializing in Generative AI and MLOps
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Mid-level AI/ML Data Engineer specializing in data pipelines, MLOps, and LLM/RAG systems
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
Mid-level AI/ML Engineer specializing in recommendation, retrieval, and MLOps
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Justin Turner
Executive Technology Leader (CTO/CIO/CISO) specializing in cloud, security, and data platforms
“CTO-level technology leader with experience building end-to-end tech strategy and roadmaps, modernizing legacy environments in healthcare (GenesisCare), and scaling engineering into large global teams (Amadeus). Built a DevOps organization at Syniverse for the Visibility Suite, implementing Kubernetes/Terraform/Chef automation that drove ~75% faster deployments, and is known for staying hands-on (including data center work) while leading strategically.”
Sri Lekha Kandadai
Mid-level Machine Learning Engineer specializing in MLOps, monitoring, and multimodal AI
“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”