AI Principal Machine Learning Engineer (10026)

Extreme Networks is a leading technology company recognized for its commitment to diversity and innovation. They are seeking an AI Principal Machine Learning Engineer to lead the development of advanced networking solutions utilizing Generative AI, Big Data, and Machine Learning, driving innovation from concept to delivery.

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
• 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