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Build and ship an agentic AI platform using LLMs, RAG, and multi-agent orchestration on Azure, while mentoring engineers and setting GenAI technical direction.
Lead the design and deployment of scalable GenAI and Agentic AI systems, focusing on LLMOps, MLOps, and cloud-native infrastructure for enterprise-grade applications.
Design and lead Aperam’s enterprise-wide AI transformation, architecting scalable ML solutions across cloud and on-premise while aligning business needs with technical execution.
Lead a team to design, prototype, and deploy AI/ML, generative AI, and cloud-native solutions for healthcare use cases on AWS and GCP, ensuring compliance and scalability.
Leads a team to build and modernize cloud-native clinical data platforms and AI solutions for Johnson & Johnson’s R&D and healthcare innovation, ensuring scalable, compliant, and AI-ready data assets.
Build and deploy GenAI and ML systems for natural language understanding, data extraction, and information retrieval at enterprise scale within S&P Global’s financial-intelligence products.
Architect and build cloud-native, AI/ML-powered enterprise applications, leading end-to-end technical strategy, scalability, and MLOps/LLMOps practices.
Designs and deploys AI solutions for local governments, focusing on computer vision, deep learning, and generative AI using NVIDIA’s software and hardware stack.
Lead validation strategy for enterprise SSD firmware, architecting AI/ML-powered test frameworks and verifying NVMe features across hardware environments.
Builds and maintains full-stack insurance applications using React, Java/Spring Boot, and Python, with cloud-native deployments on Azure/AWS and DevOps practices.
Build and operate a secure, scalable AI platform to deploy and manage LLM services across providers, ensuring high availability, cost efficiency, and enterprise-grade governance for legal-tech products.
Build and deploy ML models in Azure ML Studio to predict pensions/insurance outcomes, then set up MLOps pipelines for monitoring, retraining, and CI/CD in a regulated financial services firm.
Build and deploy production-grade AI systems, including LLMs, RAG pipelines, and agentic workflows using Python, PyTorch, and Hugging Face.
Senior Data Scientist at S&P Global designing and building GenAI-driven and ML-powered products for natural language understanding, data extraction, and information retrieval solutions. Core technologies include large language models, Python, MLOps, and NLP architectures.
Lead AI and data-science standards for a large retail/e-commerce platform, defining reusable ML patterns, MLOps lifecycles, and customer-data governance while enabling teams to scale personalization and experimentation.
Lead a team building AI-driven enterprise search and analytics for legal, tax, and compliance professionals using RAG, agents, and full-stack web tech.
Lead the design and scaling of enterprise-grade AI systems, including RAG pipelines and autonomous agents, for legal, tax, and compliance domains using Python, PyTorch, and cloud-native architectures.
Build and deploy ML models to improve product recommendations, search ranking, and customer experience for an online furniture retailer using Python, SQL, and GCP tools.
Lead cloud architect designs enterprise-grade Azure and Databricks data platforms for financial clients, building scalable ETL pipelines, governance frameworks, and MLOps patterns while guiding engineering teams.
Build and deploy production ML systems for ranking, recommendations, and personalization that directly impact revenue and customer experience at a large adtech platform.
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