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# Senior Data Scientist-Gen AI, Machine Learning (10483)

- **Company:** Extreme Networks
- **Location:** San Jose, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Machine Learning, Azure Machine Learning, Software Deployment, Graph Neural Networks, Retrieval-Augmented Generation, Transfer Learning, Apache Spark, Generative AI, Agentic-AI, Pyspark, Information Technology, Apache Flink, Apache Kafka, Free and Open-Source Software, Machine Learning Operations, Graph RAG
- **Published:** October 9, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pq00r8pcq7

## About the Role

* 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, * 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

## Description

* 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