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Jeremy Jacobson
Jeremy, lead developer and solutions architect for AI within Ricoh USA’s Intelligent Business Platform (IBP) services, is a driving force behind cutting-edge AI solutions for organizations. With research experience at renowned institutions such as Emory University and the Fields Institute, he leverages a deep well of expertise to deliver impactful, innovative results.
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Shreya Tumati
Shreya is a generative AI engineer with experience designing and deploying production-grade AI systems across insurance, healthcare, and financial services. Focusing on end-to-end GenAI solutions, Shreya builds retrieval-augmented generation (RAG) pipelines, fine-tunes large language models, and develops autonomous agents. She also architects cloud-native AI platforms on AWS, Azure, and Google Cloud Platform (GCP) to ensure scalability, reliability, and operational efficiency.
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Vishnu Anurag Thonukunoori
Vishnu is an AI/ML engineer with 5+ years of experience building scalable machine learning and generative AI solutions for enterprises. He specializes in LLMs, RAG pipelines, and AWS-based deployments and has had proven success in NLP, prompt engineering, and vector search. Vishnu is trusted by clients across insurance, eCommerce, and sustainability sectors for delivering production-grade AI systems that drive business value.
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Ishita Mukherjee
At Royal Bank of Canada, Ishita led the architecture and delivery of an enterprise agentic AI platform supporting 100+ business users. She is a principal engineer and architect with over 15 years of experience in data and AI/ML for financial services and healthcare. Ishita's expertise spans AWS, Databricks, and Python; she reduced infrastructure costs by 60% while at RBC.
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Enes Gokce
Enes is a data scientist with eight years of experience in machine learning (ML) and natural language processing (NLP). He has a demonstrated history of working with deep learning and extensive experience programming in Python and R. His areas of professional interest include generative AI (GenAI), large language models (LLMs), and hybrid AI solutions with retrieval-augmented generation (RAG) systems.
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Tomislav Slaviček-Car, mag. inf.
Tomislav is a goal-oriented developer and project manager. Highly creative and versatile, he takes pride in delivering clean and maintainable code using Python. Tomislav's portfolio includes projects in machine learning, NLP, and web app back-end development and deployment. His work experience entails 4+ years of experience with Python, including Jupiter and Amazon Sagemaker, Django framework, and 2+ years of experience in product management and managing a distributed team.
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Flavia Giammarino
Flavia has a PhD in statistics with 15+ years of experience specializing in machine learning and artificial intelligence systems for time series data. Before independent consulting, she worked as a quantitative analyst in investment banking in London at Bank of America, Deutsche Bank, and Barclays.
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Andrei Dore
Andrei is a machine learning engineer with over six years of experience. His projects have included computer vision, natural language processing, time series forecasting, classification, and regression. Andrei has deployed machine learning models on AWS cloud and developed REST services for machine learning models.
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Medhat Elhady
Medhat is an AI engineer with 3+ years of experience designing and deploying machine learning and generative AI solutions. His expertise spans AWS, Terraform, and MLOps automation, with notable work at RackSpace and Telecom Egypt. Medhat reduced ML deployment time by 70% through automated Terraform workflows and led migrations to Amazon SageMaker for improved resource management.
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Fatih Polatli
Fatih is a solutions and AI architect with nearly 20 years of experience specializing in high-availability, cloud-native systems. He leads full-stack development using Java Spring Boot, Node.js, and modern front-end frameworks such as Angular and React. An expert in AWS and GCP, Fatih integrates advanced AI solutions, including RAG, agentic AI, and LLM fine-tuning. His career spans leadership roles in aviation, eCommerce, and fintech across Europe and the United States.
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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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