Machine Learning Engineer Job Seattle Washington USA,Software Development

Position: Staff Machine Learning Engineer (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.

Become part of something big with Extreme! As a global networking leader, learn why there is no better time to join the Extreme team.

Position details

Title of position: Staff Machine Learning Engineer

Position type: Full time

Location: Seattle, WA

Position reports to: Principal Machine Learning Engineer

Final date to receive applications:Applications are being accepted on a rolling basis and this posting will remain open until filled.

Work authorization: Applicants must have legal authorization to work in the country where the role will be performed.

Job Title:

Staff Machine Learning Engineer – Gen AI, Machine Learning, Graph ML, Big Data
Experience:

8+ Years
Location:

Seattle, WA – Hybrid
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.

MS or PhD in Computer Science or equivalent experience in ML.
Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.).
Experience with No

SQL and document databases.
Proven ability to handle big data, optimize workflows, and improve system performance.
Come work with a team of highly talented engineers, and advance with us to achieve new heights every day!

Extreme Networks, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are committed to taking affirmative action to employ and advance in employment qualified protected veterans, including disabled veterans, recently separated veterans, active‑duty wartime or campaign badge veterans, and Armed Forces service medal veterans.

Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (for example, stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks. We encourage people from underrepresented groups to apply.

Benefits and total rewards:

Extreme Networks offers a comprehensive benefits package. Specific benefits vary by country and may include:

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

Benefits eligibility is based on country of employment, role, and employment status. Complete benefits details will be provided during the interview process and in the formal offer of employment.

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