Principal Data Scientist-Gen AI, Machine Learning (10042)

Principal 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

Define and drive the long-term data science and ML strategy, influencing both product direction and organizational priorities

Lead high-impact research initiatives in ML, GenAI, and Graph ML, push the boundaries of applied science, and establish best practices for scalable adoption

Partner with engineering and product leadership to align data science innovation with business goals, shaping platform and infrastructure investments

Mentor and guide staff- and senior-level scientists, set technical direction, and foster a culture of excellence and innovation

Represent the organization externally through publications, talks, and collaborations, strengthening the company’s thought leadership in AI and ML

Requirements:

Degree in Computer Science, Mathematics, or a related field

8+ years of experience in applied ML research and production deployment

3+ years of hands-on experience building Generative AI solutions such as RAG, AI Agents, or LLM fine-tuning in production

Experience with Graph ML and Graph technologies such as GNNs or GraphRAG in production

Proven track record of end-to-end ownership including design, experimentation, validation, deployment, and scaling of ML systems

Experience deploying solutions on cloud platforms such as AWS, Azure, or GCP

Demonstrated 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 distributed Big Data and ML platforms such as Spark, Flink, Kafka, PySpark, or Lakehouse

Recognized track record in the ML and AI community through publications, patents, open-source contributions, or conference talks

Strong ability to influence at the organizational level by driving strategy and fostering cross-functional alignment

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.