Senior Machine Learning Engineer (10187)

Extreme Networks•Washington, DC

134d•$170,000•Onsite

About The Position

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, driving innovation from concept to delivery. 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.

Requirements

Degree in Computer Science, Mathematics, or a related field
5+ years of experience across the full SDLC: design, coding, reviews, testing, deployment, and operations
5+ years of experience architecting and deploying end-to-end ML solutions in production environments
Proven expertise developing Generative AI solutions such as RAG, AI Agents, and LLM fine-tuning at scale
Strong background in building and operating large-scale distributed systems on cloud platforms such as AWS, Azure, or GCP
Demonstrated ability to solve highly complex and ambiguous problems, setting direction for others

Nice To Haves

MS or PhD in Computer Science, Machine Learning, or a related discipline
Experience with Graph ML and graph technologies such as GNNs or Graph RAG
Deep expertise with distributed Big Data technologies such as Spark, Flink, Kafka, PySpark, Lakehouse, Druid, Hudi, or Glue
Track record of mentoring engineers and influencing cross-team initiatives

Responsibilities

Serve as a thought leader and forward thinker, setting the technical vision and driving innovation across products and platforms.
Shape long-term strategy by designing and launching strategic ML solutions that deliver company-wide impact.
Own and guide the full software development lifecycle at scale, including architecture, design, testing, deployment, and operations.
Lead technical discussions, define best practices, and ensure engineering rigor through design and code reviews.
Architect and deliver high-performance, production-grade ML platforms and frameworks, enabling next-generation real-time ML and Generative AI systems.
Partner with senior engineers, scientists, and cross-functional leaders to accelerate experimentation, validation, and model integration, ensuring solutions are robust, scalable, and aligned with business goals.