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Build and operate a secure, scalable AI platform for enterprise clients in regulated financial services, enabling teams to deploy, govern, and scale AI-powered applications using cloud-native infrastructure and AI services.
Builds enterprise-grade Angular frontends with AI integrations, CMS pipelines, and design systems for global clients while collaborating with US and European teams.
Builds AI-powered web apps and data pipelines using FastAPI/React on GCP/Azure, integrates with LLM APIs, and optimizes prompt engineering and model performance.
Build and deploy production-grade AI/ML models (LLMs, NLP, CV, forecasting) to solve complex business problems, using Python, TensorFlow/PyTorch, and cloud ML platforms.
We are looking for a DevOps Engineer with solid experience in CI/CD pipeline automation, cloud infrastructure management, and container orchestration. The ideal candidate will be proficient in Azure DevOps with Git…
Join NTT DATA and shape the future of digital innovation At NTT DATA , we are a global technology consulting company helping organizations transform through innovation, technology, and collaboration. With more than…
Build and deploy AI/ML models for vision, audio, and language tasks using PyTorch/TensorFlow and cloud MLOps tools.
Build and scale the enterprise DevOps operating model for GXO’s Agentic AI Platform on GCP and Kubernetes, owning secure CI/CD, Terraform infrastructure, and AI model-serving pipelines.
Designs and deploys production-grade generative AI solutions (LLMs, RAG, AI agents) for enterprise clients, using frameworks like LangChain and cloud platforms like Azure OpenAI, with a focus on scalability, security, and cost efficiency.
Lead data engineering for a digital bank, building scalable pipelines and Lakehouse solutions in Google Cloud to enable analytics and decision-making.
Build and deploy ML/AI models (classical, deep learning, LLMs) with MLOps/LLMOps pipelines, focusing on production-grade solutions and API integration for enterprise use.
Design and lead enterprise-scale AI/ML architectures, including Generative AI and Agentic AI systems, ensuring scalability, security, and MLOps/LLMOps best practices.
Lead AI/ML teams to build, deploy, and govern production-grade generative and agentic AI systems using LLMs, RAG, and orchestration tools.
Builds and deploys ML/DL models (classical, deep learning, LLMs) for structured/unstructured data, focusing on MLOps/LLMOps pipelines, model monitoring, and AIOps automation in a telecom/enterprise context.
Job Description: About Us At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our…
Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens…
Leads AI/ML architecture and development for Pfizer’s commercial analytics, designing RAG pipelines, agentic systems, and production-grade AI solutions to optimize marketing spend and business strategy.
Build and deploy production-grade AI agents and RAG systems to optimize Pfizer’s commercial marketing spend and workflows, using Python, cloud LLMs, and agent frameworks like LangChain.
Build and maintain scalable ML pipelines and infrastructure for AI-driven projects using Docker, Kubernetes, and cloud platforms like AWS/GCP/Azure.
Build and deploy NLP and generative AI systems—fine-tuning LLMs, RAG pipelines, and vector search—to automate document processing and decision support for a mid-market professional services firm.
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