Extreme NetworksRemote
AI Principal Machine Learning Engineer (10189)
United States
Full Time
2 hours ago
00$170,000 USD
H1B Sponsor Likely
Key skills
AIMachine LearningMLGenerative AILLMRAGSparkKafkaAWSAzureGCPSDLCLeadershipCollaboration
About this role
Extreme Networks is a leading technology company focused on innovating with Generative AI and building next-gen networking experiences. The AI Principal Machine Learning Engineer will provide technical leadership for large-scale distributed systems and drive innovation in Big Data and AI technologies, shaping the product vision and technical roadmap.
Responsibilities:
- Provide technical leadership and vision for large-scale distributed systems, ML platforms, and next-generation data infrastructure
- Lead the design, architecture, and delivery of end-to-end solutions across the full SDLC, spanning development, testing, deployment, and operations
- Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready solutions
- Architect scalable microservices and real-time inferencing systems leveraging modern ML infrastructure such as AI Agents, MCP, ML Inference, and LLM Gateway
- Mentor and grow engineering teams, set technical direction, and foster a culture of engineering rigor, collaboration, and operational excellence
- Champion best practices for building resilient, secure, and high-performance systems, optimized for scale and reliability
Requirements:
- Degree in Computer Science, Mathematics, or a related field
- 10+ years of experience across the full software development lifecycle including design, coding, reviews, testing, deployment, and operations
- 5+ years of experience with distributed Big Data and ML platforms such as Spark, Lakehouse, Debezium, Kafka, Flink, or Hudi
- Hands-on experience building Generative AI solutions such as RAG, AI Agents, and LLM fine-tuning in production
- Experience working with Graph ML and Graph technologies such as GNNs
- Strong track record of end-to-end solution ownership, from design through production scaling
- 5+ years of experience deploying large-scale solutions on cloud platforms such as AWS, Azure, or GCP
- Proven ability to solve highly complex, ambiguous, cross-domain problems with measurable business impact
- MS or PhD in Computer Science, Machine Learning, or a related discipline
- Experience with sensitive or streaming data pipelines, including real-time compliance and governance controls