Principal Machine Learning Engineer (10187)

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.

Responsibilities

Pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning; Building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time

Requirements

Degree in mathematics/computer science or related discipline; 10+ 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

Nice to have

MS or PhD in Computer Science or equivalent experience in ML; Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.); Experience with NoSQL and document databases; Proven ability to handle big data, optimize workflows, and improve system performance

Benefits

Medical, dental, and vision insurance; Flexible work schedules and work-from-home opportunities where role permits; Paid time off, including open time off in eligible markets and statutory leave in all markets; Paid holidays in accordance with local practice; Retirement savings programs, including RRSP matching in Canada; Employee Stock Purchase Program, where eligible; Employee assistance program; Tuition reimbursement, where eligible