Staff Machine Learning Engineer -Gen AI, Machine Learning, Graph ML, Big Data - 10030

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.
Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.
Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team.
Position: Staff Machine Learning Engineer -Gen AI, Machine Learning, Graph ML, Big Data
Experience: 8 to 14  Years
Position type: Full-time

Location: Bangalore/Remote

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.

Degree in mathematics/computer science or related discipline.
8+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
6+ years of experience in Python with an in-depth knowledge of its advanced features and libraries.
Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI.
Proficient in Docker, Kubernetes, and modern CI/CD practices.
4+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
Experience as a mentor, tech lead or leading an engineering team.