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Saipriya Puram
Saipriya has spent over 10 years building scalable data architectures and deploying machine learning models across technology and healthcare. Her toolkit centers on Databricks, AWS, and advanced analytics. While at Tesla, Saipriya achieved a 74% increase in processing speed by innovating data processing techniques.
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RAJ KUMAR G
Across healthcare, manufacturing, and engineering, Raj has spent 17 years building production-grade generative AI and data systems. His toolkit centers on AWS Bedrock, Azure Databricks, and MLflow. While at Parker Hannifin Corporation, Raj delivered a $10+ million RAG layer for global industrial operations.
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Faizy Ahsan
He is a senior machine learning engineer with over six years of experience in distributed data processing and production-scale ML systems. His expertise spans Databricks, AWS, and Docker for aerospace, adtech, and healthcare industries. At Pratt & Whitney Canada, Faizy architected and led the modernization of ML infrastructure, reducing model deployment time by 60%.
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Surya Kant Swain
For the past 15 years, Surya has built production software and AI systems across engagements with banking, technology, and retail. His work centers on Python, AWS, and Kubernetes. He raised customer self-service rates by 27% while at Wells Fargo through production LLM evaluation infrastructure and chatbots.
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Parham Hamouni
Parham is a senior LLM engineer and PhD researcher with 6+ years of shipping production AI systems across manufacturing, legal, and finance. At Toronto Metropolitan University, his PhD applies DPO and RLHF to temporal graph reasoning, achieving 83% pairwise accuracy and outperforming baselines by 12–15pp. In production, Parham works with RAG pipelines, fine-tuned transformers (FinBERT, Qwen, LLaMA-2), and full MLOps stacks. At Kraft Heinz, his RAG system cut troubleshooting time by 30%.
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Clayton Lemons
Clayton is a transformative software engineer and leader with over 15 years of experience in the software industry, innovating at the intersection of data, AI/ML, and cloud engineering. As both an individual contributor and a visionary leader, he is a dynamic force in transforming challenges into user-centric, high-quality software solutions. Renowned for his technical mastery, strategic foresight, and principled approach to software, Clayton elevates teams to collaborate and perform their best.
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Arthur Gaia
Arthur is a data scientist and machine learning (ML) engineer specializing in production ML, MLOps, and cloud solutions. He builds scalable ML pipelines, back-end APIs, and automated model lifecycles using Databricks, MLflow, Docker, Kubernetes, and AWS/Azure. Arthur has developed a forecasting system with 75-85% monthly accuracy supporting sales and operations planning (S&OP).
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Merna Hesham
Merna is an AI engineer and technical project manager with six years of experience in machine learning and MLOps for Valeo, Weight Watchers US, Accenture, and Egypt's Ministry of Communications and IT. She works across the full delivery path, scoping and resourcing the project, building the pipeline in Python, Docker, Kubernetes, and MLflow, then running it on GCP or AWS. Merna has trained over 500 engineers in the same practices she deploys.
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Dauren Baitursyn
Dauren is an AI engineer with 8+ years of experience building production ML systems, from LLM-powered applications to distributed training pipelines. He specializes in NLP (BERT, GPT, spaCy), conversational AI (Rasa, RAG), and MLOps (MLflow, Ray). He's built systems processing millions of records with LLM classification, semantic search, and ensemble forecasting. With a CS degree from KAIST (top 50 QS), Dauren delivers end-to-end AI solutions from research to production.
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Anzor Gozalishvili
Anzor is a senior machine learning and MLOps engineer with 8+ years of experience building production ML systems, data pipelines, and cloud infrastructure. He has designed ML platforms with Dagster, W&B, MLflow, Spark, AWS, and Azure and built agentic systems using LangGraph, RAG, vector search, and MCP. His background spans NLP, document intelligence, deep learning, bioinformatics, and large-scale model training. He is also a published researcher in NLP and computational biology.
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Chaima YEDES
Chaima is a data architect with 8 years of experience across data engineering, MLOps, and AI infrastructure. She's a specialist in trusted lakehouses, federated data platforms, and AI-ready foundations. At QData (ADQ), she built a Databricks-native quality framework across multiple entities, and at Valeo, she led the AI data platform for autonomous driving across 4 countries.
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