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Senior Machine Learning Engineer (10187)
- Seattle, Washington, United States
- Seattle, Washington, United States
Über
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: Senior Machine Learning Engineer
Position type: Full time
Location: Seattle, WA
Position reports to: Staff Machine Learning Engineer
Application deadline: 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.
About the Position
Position : Senior Machine Learning Engineer -Gen AI, Machine Learning, Graph ML, Big Data
Experience : 4+ Years
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.
Required Skills & Expertise
Degree in mathematics/computer science or related discipline.
4+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
4+ 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.
2+ 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.
Preferred Qualifications
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.
Come work with a team of highly talented engineers, and advance with us to achieve new heights every day!
Equal Employment Opportunity
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‑day war 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.
$110,000 - $160,000 a year
This role offers a market‑competitive salary with an anticipated base compensation range of 110,000 to 160,000 USD. Actual compensation will depend on the selected candidate’s experience, qualifications, skills, and work location. The posted range reflects the amount Extreme Networks reasonably and in good faith expects to pay upon hire. This range is determined using objective, gender‑neutral criteria based on skills, experience, responsibility, and working conditions. In addition to base pay, this role is eligible for a performance‑based bonus and the full benefits package described below.
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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Sprachkenntnisse
- English
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