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Senior Machine Learning Engineer (10187)
Отличная вакансия в стабильной публичной компании с четким фокусом на инновации (GenAI). Предлагается работа над 'greenfield' проектами, конкурентная зарплата и возможность влиять на стратегию продукта.
Сложность вакансии
Роль требует глубокой экспертизы как в классическом ML, так и в современных технологиях GenAI (RAG, агенты), а также навыков проектирования высоконагруженных распределенных систем. Высокий уровень ответственности за архитектуру и лидерство в команде повышают планку требований.
Анализ зарплаты
Предложенная зарплата до $170,000 находится в рамках рыночного диапазона для Senior ML ролей в США, однако для Сиэтла (крупного технологического хаба) она ближе к нижней или средней границе, учитывая высокие бонусы в BigTech компаниях региона. Тем не менее, пакет бенефитов может сделать предложение более конкурентоспособным.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Machine Learning Engineer position at Extreme Networks. With over five years of experience in architecting and deploying end-to-end ML solutions, I am particularly drawn to your AI Core group's work on multi-agent systems, RAG, and LLM fine-tuning. My background in building production-grade ML platforms on cloud infrastructure aligns perfectly with your mission to redefine network management through Generative AI.
In my previous roles, I have successfully led the development of large-scale distributed systems and implemented complex AI agents that solve real-world problems. I am excited about the "greenfield" opportunity at Extreme to shape the technical roadmap for next-gen networking. My expertise in Spark, Kafka, and cloud-native ML deployment will allow me to contribute immediately to your high-performance platforms and drive innovation from concept to delivery.
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Откликнитесь в extremenetworks уже сейчас
Присоединяйтесь к лидеру сетевых технологий и создавайте будущее Generative AI в Extreme Networks уже сегодня!
Описание вакансии
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.
Senior Software Engineer (GenAI, ML):
Experience: 5+ Years
Location: Seattle, Washington
Are you energized by the idea of innovating with Generative AI? Do you want to create global impact while tackling challenges at the forefront of Artificial Intelligence? Do you dream of building ground-breaking products that define the future of AI-driven network management? Then come, advance with us at Extreme.
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.
There has never been a better time to join Extreme. With multiple acquisitions expanding our portfolio and market strategy, we are experiencing unprecedented growth worldwide. Recognized as a Technology Leader in the Gartner Magic Quadrant and a multi-year Best Employer award winner, Extreme is committed to a culture of diversity, inclusion, and equality, where every employee thrives because of their differences, not despite them.
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.
Job 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.
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
Preferred Qualifications
· 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
Salary based on qualifications, experience and region up to USD 170000 plus benefits.
Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.
We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on “protected categories,” Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.
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Навыки
- AWS
- Azure
- Python
- Machine Learning
- LLM
- Graph Neural Networks
- MLOps
- RAG
- Google Cloud Platform
- PySpark
- Apache Spark
- Distributed Systems
- Big Data
- Generative AI
- Apache Kafka
Возможные вопросы на собеседовании
Вакансия делает упор на разработку AI-агентов и RAG для сетевых задач.
Расскажите о вашем опыте проектирования систем RAG: как вы решали проблемы актуальности данных и галлюцинаций в контексте специфических доменных знаний?
Требуется опыт работы с распределенными системами и Big Data.
Как бы вы спроектировали архитектуру для обработки телеметрии сети в реальном времени с использованием Spark или Kafka для последующего обучения ML-моделей?
Позиция Senior предполагает участие в полном жизненном цикле разработки.
Опишите ваш подход к обеспечению воспроизводимости и мониторинга ML-моделей в продакшене (MLOps). С какими трудностями вы сталкивались при масштабировании?
В предпочтительных требованиях указаны Graph ML и GNN.
В каких сценариях сетевого управления использование графовых нейронных сетей (GNN) дает преимущество перед традиционными методами анализа данных?
Роль подразумевает лидерство и менторство.
Приведите пример, когда вам приходилось принимать сложное архитектурное решение в условиях неопределенности. Как вы убеждали команду и стейкхолдеров в правильности выбора?
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