AI and Machine Learning Engineer

AI and Machine Learning Engineer This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

At  HPE Networking , the  Digital Experience & Automation (DEA)  team is reimagining how people experience support and services in a digital‑first world—setting new standards for the future of networking. We enable customers, partners, and employees through AI‑driven tools and modern platforms, transforming support into a unified, efficient, and simple experience that drives measurable value. Our mission is grounded in  innovation with purpose : applying automation, AI, and data‑driven insights to simplify journeys, reduce friction, and create meaningful outcomes at every touchpoint. The AI/ML Engineer designs and builds scalable, production-grade AI/ML solutions for mission-critical cloud applications. This role requires ownership of the complete machine learning lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and continuous improvement.   The engineer applies advanced technical expertise to architect, prototype, and implement AI/ML and GenAI-driven cloud solutions using modern   MLOps   practices for reliable, reproducible, and secure deployments.   Management Level Definition:   Applies advanced subject matter expertise to solve complex technical and business problems. Works independently on end-to-end AI/ML systems and contributes to architectural decisions. Provides technical leadership, mentors team members, and drives best practices across cross-functional teams.

Design   moderate to complex   AI/ML based cloud application features as per specifications.   Develop, train, evaluate, and deploy ML/DL models.   Build GenAI applications using LLMs, RAG, and Agent workflows.   Develop data pipelines and AI services/APIs.   Implement   MLOps   and   LLMOps   practices for deployment and monitoring.   Evaluate model and application performance using AI observability tools.   Collaborate with business and engineering teams to deliver AI solutions.   Develops and maintains GenAI / cloud application modules adhering to security policies.   Designs test plans, develops, executes, and automates test cases for assigned portions of the developed code.   Deploys code and troubleshoots issues in application modules and the deployment environment.   Shares and reviews innovative technical ideas with peers, high-level technical contributors, technical writers, and managers.   Knowledge and Skills   Python, SQL, Data Analysis   Machine Learning and Deep Learning (Scikit-learn,   PyTorch /TensorFlow)   LLMs, Prompt Engineering, RAG   LangChain ,   LangGraph ,   LlamaIndex   (or similar frameworks)   Vector Databases and Semantic Search ( Weaviate , Pinecone,   Qdrant ,   pgvector , etc.)   AI Evaluation & Monitoring ( MLflow ,   Langfuse ,   OpenTelemetry   (basic understanding),   Arize   Phoenix)   Docker, Kubernetes, CI/CD . Understanding DevOps practices like continuous integration/deployment and orchestration with Kubernetes.   AWS, Azure, or GCP   Experience with design methodologies, cloud-native applications, developer tools, managed