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Lead a team to build Snowflake-native AI platforms and autonomous agents that power data-driven decisions in rare disease commercial operations, using Cortex AI and Snowpark for production-grade ML and agent systems.
Design and build AI-ready data pipelines and products that power retrieval-augmented AI systems, ensuring data quality, governance, and secure access for AI models.
Lead a team of data scientists and AI engineers to design, build, and deploy AI solutions that drive business performance and operational efficiency using Python, SQL, and modern ML frameworks.
Build and deploy AI/ML models for healthcare claims processing using PyTorch/TensorFlow, MLOps pipelines, and cloud tools to reduce payment inaccuracies and waste.
Build, deploy, and monitor AI/ML models and MLOps pipelines for federal missions, integrating NLP, LLMs, and predictive analytics into secure enterprise systems.
Build and deploy production-grade AI services and integrations in Python, integrating models into enterprise systems like ERP/CRM and ensuring scalable, secure AI adoption.
Principal ML Engineer designs, builds, and deploys production-grade AI systems using LLMs and deep learning, integrating agent workflows across GCP, AWS, and Azure.
Lead a team building generative AI and agentic systems for healthcare, including LLMs, RAG, and AI agents, from prototyping to production with MLOps and Responsible AI practices.
At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of…
Leads engineering teams to design and deliver cloud-native financial platforms, driving cross-product collaboration and aligning tech strategy with JP Morgan Chase’s fintech goals.
Lead the security architecture for JPMorganChase’s AI/ML platforms, designing controls against threats like prompt injection and data poisoning while guiding secure AI agent development and deployment.
Build, train, and deploy ML models using Python and frameworks like TensorFlow/PyTorch to power AI-driven business solutions.
Build ML models and data pipelines to optimize retail decisions like personalization and real-time analytics using Python, Spark, and AWS.
Design and implement cloud security architectures, automate controls, and secure AI/ML platforms across AWS and Azure while embedding security into CI/CD and MLOps pipelines.
Designs scalable AI-enabled workflow platforms and agentic automation for Daimler Truck’s engineering environments, integrating model serving, enterprise systems, and CI/CD pipelines.
Builds and deploys AI-powered applications by integrating LLMs, developing full-stack features (React/Next.js frontends, FastAPI/Flask backends), and optimizing RAG pipelines with vector databases for scalable, production-ready solutions.
Lead AI/ML architecture and development for fintech products, building and deploying production-grade generative AI systems including LLMs and RAG pipelines.
Build and deploy scalable ML pipelines, real-time/batch inference systems, and LLM serving stacks for a fintech personalization engine in AWS.
Designs and builds scalable data pipelines and backend services to ingest, process, and manage data for U.S. federal agencies using Python/Node.js, APIs, and ETL workflows.
Build and deploy production-grade generative AI systems—LLMs, RAG, and AI agents—to automate document processing, customer support, and decision workflows in a regulated banking environment.
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