AI Principal Machine Learning Engineer (10189) at extremenetworks

AI Principal Machine Learning Engineer – (Gen AI, Big Data): Are you energized by the idea of innovating with Generative AI? Do you want to create global impact while tackling challenges at the forefront of Artificial Intelligence? Do you dream of building ground-breaking products that define the future of AI-driven network management? Then come, advance with us at Extreme. This is a greenfield opportunity to shape next-gen networking experiences at the cutting edge of Generative AI, Machine Learning, Big Data, and Cloud Computing. You will help define every aspect of the user journey, product vision, and technical roadmap, and you will drive innovation from concept to delivery. There has never been a better time to join Extreme. With multiple acquisitions expanding our portfolio and market strategy, we are experiencing unprecedented growth worldwide. Recognized as a Technology Leader in the Gartner Magic Quadrant and a multi-year Best Employer award winner, Extreme is committed to a culture of diversity, inclusion, and equality, where every employee thrives because of their differences, not despite them. Our AI Core group is pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship Extreme products while enabling entirely new offerings. Together, we are driving a fundamental shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Extreme, innovation is not just encouraged, it is expected. Advance with us and help shape the future of network intelligence. Job Responsibilities • Provide technical leadership and vision for large-scale distributed systems, ML platforms, and next-generation data infrastructure • Lead the design, architecture, and delivery of end-to-end solutions across the full SDLC, spanning development, testing, deployment, and operations • Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready solutions • Architect scalable microservices and real-time inferencing systems leveraging modern ML infrastructure such as AI Agents, MCP, ML Inference, and LLM Gateway • Mentor and grow engineering teams, set technical direction, and foster a culture of engineering rigor, collaboration, and operational excellence • Champion best practices for building resilient, secure, and high-performance systems, optimized for scale and reliability Requirements • Degree in Computer Science, Mathematics, or a related field • 10+ years of experience across the full software development lifecycle including design, coding, reviews, testing, deployment, and operations • 5+ years of experience with distributed Big Data and ML platforms such as Spark, Lakehouse, Debezium, Kafka, Flink, or Hudi • Hands-on experience building Generative AI solutions such as RAG, AI Agents, and LLM fine-tuning in production • Experience working with Graph ML and Graph technologies such as GNNs • Strong track record of end-to-end solution ownership, from design through production scaling • 5+ years of experience deploying large-scale solutions on cloud platforms such as AWS, Azure, or GCP • Proven ability to solve highly complex, ambiguous, cross-domain problems with measurable business impact Preferred Qualifications • MS or PhD in Computer Science, Machine Learning, or a related discipline • Experience with sensitive or streaming data pipelines, including real-time compliance and governance controls • Salary based on qualifications, experience and region up to USD 170000 plus benefits.