Extreme NetworksRemote
Senior Software Engineer (Generative AI/Machine Learning) (10029)
United States of America
Full Time
4 weeks ago
00$170,000 USD
H1B Sponsor Likely
Key skills
AIMachine LearningMLGenerative AILLMRAGSparkKafkaAWSAzureGCPGlueSDLCMentoring
About this role
Extreme Networks is a global networking leader that provides end-to-end, cloud-driven networking solutions. They are seeking a Senior Software Engineer to innovate with Generative AI and Machine Learning, driving the development of next-gen networking experiences and solutions.
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