Staff Data Scientist (10029)

Overview

Staff Data Scientist (Gen AI, Machine Learning) :

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

• Serve as a thought leader, shaping long-term ML strategy and driving innovation across products and platforms
• Lead research and development of novel ML, GenAI, and Graph ML techniques, and translate cutting-edge research into scalable production systems
• Guide end-to-end solution development including model design, experimentation, validation, deployment, and operations at scale
• Mentor engineers and scientists, fostering a culture of technical excellence and cross-functional collaboration
• Extend ML libraries, frameworks, and infrastructure to accelerate experimentation and production integration

Requirements

Preferred Qualifications

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