The Role
Lead strategy and research for Generative AI and Graph ML, drive end-to-end ML system design and production deployments, mentor scientists, align ML innovation with product goals, and represent the company externally.
Summary Generated by Built In
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
Skills Required
- Degree in Computer Science, Mathematics, or a related field
- 8+ years of experience in applied ML research and production deployment
- 3+ years 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
- 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
Extreme Networks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Extreme Networks and has not been reviewed or approved by Extreme Networks.
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Flexible Benefits — Flexible work options and time‑off policies are emphasized through a 'Flex First' model with remote/hybrid choices and flexible or unlimited PTO. Wellness programs, volunteer time, and family leave round out a broad, adaptable package.
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Healthcare Strength — Healthcare coverage is positioned as comprehensive, including medical, dental, vision, mental health, and HSA eligibility. U.S. high‑deductible plans include a company HSA contribution, strengthening the financial value of coverage.
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Equity Value & Accessibility — Equity participation is accessible via RSUs and an ESPP that enables discounted stock purchases. Variable pay and equity components can materially lift total compensation when business performance is strong.
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The Company
What We Do
Extreme Networks, Inc. (EXTR) is a leader in cloud networking focused on delivering services that connect devices, applications, and people in new ways. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.
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