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Lead AI-driven transformation for global manufacturing and supply operations, deploying agentic systems and LLMs to optimize processes and KPIs across Opella’s network.
Designs and implements AI/ML and generative AI solutions for enterprise clients, focusing on architecture, LLM/RAG pipelines, and MLOps—collaborating with data and product teams to scale AI from proof-of-concept to production while ensuring security, governance, and cloud platform integration.
Architect and implement generative AI solutions on SAP BTP, designing RAG pipelines, knowledge graphs, and LangChain orchestration to embed LLMs into enterprise SAP applications.
Pre-sales AI Solutions Architect designs and pitches AI solutions (ML, GenAI, RAG, MLOps) to UK clients, leads bids, and represents Sopra Steria at industry events.
Lead AI engineering for generative-AI copilots and RAG systems in a regulated financial-services environment, building production-grade Python/LLM pipelines on Azure.
Lead a team of engineers to design, build, and deploy AI and automation solutions for Amgen’s AI Studio, turning business challenges into scalable, production-ready products with measurable impact.
Build and deploy ML models to optimize healthcare copay programs and extract insights from pharmaceutical data using Python, R, and MLOps tools.
Build and deploy Python-based AI and analytics solutions to transform financial data into actionable insights for Parameta Solutions, leveraging AWS and generative AI.
Designs and leads AI-driven customer care systems at scale, integrating Python-based ML models into production while ensuring seamless human-in-the-loop fallbacks for complex queries.
Build, deploy, and monitor ML/AI models in Python using TensorFlow/PyTorch, orchestrate pipelines with Airflow/Nifi, and scale on AWS/Databricks.
Lead the MLOps platform for autonomous-driving teams, building scalable AWS/Kubernetes pipelines with Ray, Airflow, and MLflow to train and deploy perception models in safety-critical automotive systems.
Lead the build and operation of MLOps platforms on AWS for autonomous-driving ML workloads, using Ray, Kubernetes, Airflow, and MLflow to ensure reproducible, traceable, and auditable pipelines.
Design and implement scalable MLOps/LLMOps pipelines on AWS, including SageMaker, EKS, and CI/CD, to deploy and monitor production-grade AI models for enterprise clients.
Lead a team building secure, scalable financial platforms using cloud-native tools and advanced programming to deliver trusted products for JPMorgan Chase.
Lead the design and operation of cloud infrastructure and CI/CD pipelines for AI and financial-data platforms, ensuring reliability, security, and developer productivity at scale.
Leads AI/ML projects end-to-end, from problem definition to deployment, using Python, TensorFlow, and PyTorch to build models for forecasting, optimization, and anomaly detection, then collaborates with engineers and business teams to drive data-driven business decisions.
Develop AI/ML models to predict and optimize bead designs for proteomics workflows and diagnostic assays, bridging data science with wet-lab R&D at a global life-science tools company.
Build enterprise-grade full-stack apps using Java/Spring Boot, React, and cloud-native tools while integrating AI copilots to accelerate development and improve code quality.
Leads AI/ML engineering for Accenture, designing and deploying large-scale LLM and deep-learning solutions on Azure using Python, .NET, and cloud-native architectures while mentoring teams and driving technical strategy.
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable.…
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