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Vetted Azure Machine Learning Professionals
Pre-screened and vetted.
Mid-level Data Scientist specializing in Healthcare ML and Generative AI
Mid-level AI/ML Engineer specializing in Generative AI for logistics and industrial systems
Mid-level ML Engineer specializing in MLOps, data engineering, and GenAI/RAG systems
Mid-level ML Engineer specializing in FinTech risk, fraud, and GenAI RAG systems
Mid-level Data Scientist specializing in ML, NLP and forecasting
Mid-level Software Engineer specializing in AI/GenAI and cloud-native backend systems
Mid-level Data Scientist specializing in Healthcare ML and Generative AI
Principal AI Architect & Data Engineer specializing in GenAI, agentic systems, and MLOps
Mid-level Machine Learning Engineer specializing in MLOps and multimodal AI
Mid-level AI Software Engineer specializing in LLMs and healthcare AI
Mid-level AI/ML Engineer specializing in Generative AI and cloud MLOps
Mid-Level .NET Software Engineer specializing in cloud-native enterprise applications
Mid-level Data Analyst specializing in marketing analytics and machine learning
Mid-level Applied AI Engineer specializing in LLM agents and RAG systems
Executive Technology Leader specializing in Quantum Computing, AI, and Cloud Platforms
Vikesh Patel
Senior AI/ML Engineer & Data Scientist specializing in LLMs, RAG, and MLOps
“ML/NLP practitioner who has delivered production systems in regulated domains, including a healthcare compliance pipeline using RAG (GPT-4/Claude) plus TF-IDF retrieval that increased document review throughput 4.5x. Also has hands-on experience improving fraud detection data quality via entity resolution (Levenshtein, Dedupe.py) validated with A/B testing, and building scalable, monitored workflows with Airflow, CI/CD, and AWS SageMaker.”
Adithya Sharma
Mid-level AI/ML Engineer specializing in MLOps, NLP, and Generative AI
“Built and deployed a production LLM-powered text-to-SQL/document intelligence chatbot on AWS that lets non-technical business users query complex enterprise databases in plain English. Demonstrates deep practical expertise in schema-aware prompting, embeddings-based schema retrieval, SQL safety/validation guardrails, and rigorous offline/online evaluation with human-in-the-loop approvals for risky queries.”
Lakshmi Swathi Sreedhar
Mid-level AI Engineer specializing in Generative AI and LLM systems
“Built and deployed a production-grade, multi-agent Text-to-SQL assistant that lets non-technical stakeholders query large enterprise databases in natural language. Uses Pinecone-based schema retrieval + LLM reasoning (Gemini/Claude/GPT) with a dedicated validation agent (schema/syntax checks and safe dry runs) to reduce hallucinations and improve reliability, while optimizing latency and cost via async execution and embedding caching.”
Venkatalakshmi Kottapalli
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
“LLM engineer/data analyst who built a production RAG QA assistant over the Jurafsky & Martin NLP textbook to reduce hallucinations and provide explainable, source-grounded answers. Experienced with LangChain/LangGraph orchestration, retrieval optimization (embeddings, vector DBs, caching), and rigorous evaluation/monitoring (Retrieval@K, A/B tests, telemetry/drift). Previously communicated analytics insights to non-technical stakeholders at GS Analytics using Power BI and simplified reporting.”