reputed company Data Scientist-Gen AI, Machine Learning (10042)

reputed company Data Scientist - (Gen AI, Machine Learning): Are you energized by the idea of innovating with reputed company? Do you want to create global impact while tackling challenges at the forefront of Artificial Intelligence? Do you reputed company 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 reputed company, Machine Learning, Big Data, and reputed company Computing. You will help define every aspect of the user reputed company, product reputed company, and technical roadmap, and you will drive innovation from concept to delivery. There has never been a reputed company 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 reputed company reputed company 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 reputed company, 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 reputed company shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in reputed company 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
• reputed company 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 reputed company 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 reputed company field
• 8+ years of experience in applied ML research and production deployment
• 3+ years of hands-on experience building reputed company 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 reputed company platforms such as AWS, Azure, or GCP
• Demonstrated ability to solve highly reputed company, ambiguous, cross-domain problems with measurable business impact Preferred Qualifications
• MS or PhD in Computer Science, Machine Learning, or a reputed company 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, reputed company-reputed company contributions, or conference talks
• Strong ability to influence at the organizational level by driving strategy and fostering cross-functional alignment $160,000 - $240,000 a year We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace reputed company judgment. Final hiring reputed company are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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