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Vetted Retrieval-Augmented Generation Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in healthcare risk prediction and GenAI
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in NLP, fraud detection, and LLM applications
Mid-level Data Scientist specializing in ML, NLP, and scalable data pipelines
Mid-level AI/ML Engineer specializing in risk modeling, NLP, and Generative AI
Mid-level AI/Data Engineer specializing in LLMs, RAG pipelines, and cloud data platforms
Mid-Level Full-Stack Software Engineer specializing in distributed systems and FinTech
Senior AI Engineer specializing in LLM and generative AI production deployments
Junior Data & AI Analyst specializing in BI, LLM applications, and analytics
Mid-level Full-Stack Java Developer specializing in cloud microservices and React
Mid-level Data Engineer specializing in cloud-native ETL/ELT and Snowflake analytics platforms
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Senior Data Strategy & AI Product Consultant specializing in analytics platforms and privacy-safe measurement
Tushar Gwal
Mid-level AI/ML Engineer specializing in GenAI, computer vision, and MLOps
“AI engineer with experience taking a GPT-4-powered GenAI career coach toward production on Azure AI Foundry, re-architecting the backend with hybrid (vector + keyword) search and RAG optimizations to cut latency by 50%. Also has client-facing TCS experience building healthcare ETL pipelines and delivering error-free monthly reports, plus current work analyzing agentic system reasoning traces and guardrail drift as an AI research fellow.”
Bharath Reddy Nallu
Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps
“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”
Sai Manikanta Kasireddy
Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems
“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”
Praniket Ketan Walavalkar
Junior AI Software Engineer specializing in RAG agents and cloud data platforms
“AI Software Engineer (student employee) at University of Washington IT who helped deploy "Purple," a governed, explainable LLM platform on Azure used by 100,000+ students/faculty/staff. Independently led scalable reliability efforts by building automated agent quality/load/red-team testing and CI/CD health validation (Playwright/Node.js, Azure DevOps), and previously built an explainable AI scheduling assistant for clinical operations at Proliance Surgeons.”