Extreme NetworksRemote
Senior Software Engineer (Generative AI/Machine Learning) (10029)
United States
Full-time
1 week ago
00$170,000 USD
H1B Sponsor Likely
Key skills
Generative AIMachine LearningCloud ComputingDistributed SystemsBig Data TechnologiesEnd-to-End ML SolutionsProblem SolvingMentoringAIMLLLMSparkKafkaAWSAzureGCPGlueSDLC
About this role
Extreme Networks is a global networking leader providing cloud-driven networking solutions. They are seeking a Senior Software Engineer to innovate with Generative AI and drive the development of next-gen networking experiences.
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
- 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