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Extreme Networks

Senior AI/ML Engineer – Generative AI & Autonomous Agents (10034, 10035) Toronto, Canada - Hybrid

Extreme Networks Toronto, Canada 10 days ago
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At Extreme Networks, we create effortless networking experiences that empower people and organizations to advance. As part of our growing AI Competence Center, we are seeking a Senior AI/ML Engineerwith  expertise in Generative AI, multi-agent systems, and LLM-based application development. 
In this role, you will help build the next generation of AI-native systems that combine traditional machine learning, generative models, and autonomous agents. Your work will power intelligent, real-time decisions for network design, optimization, security, and support. 

Key Responsibilities

  • Design and implement the business logic and modeling that governs agent behavior, including decision-making workflows, tool usage, and interaction policies. 
  • Develop and refine LLM-driven agents using prompt engineering, retrieval-augmented generation (RAG), fine-tuning, or function calling. 
  • Understand and model the domain knowledge behind each agent: engage with network engineers, learn the operational context, and encode this understanding into effective agent behavior. 
  • Apply traditional ML modeling techniques (classification, regression, clustering, anomaly detection) to enrich agent capabilities. 
  • Contribute to the data engineering pipeline that feeds agents, including data extraction, transformation, and semantic chunking. 
  • Build modular, reusable AI components and integrate them with backend APIs, vector stores, and network telemetry pipelines. 
  • Collaborate with other AI engineers to create multi-agent workflows, including planning, refinement, execution, and escalation steps. 
  • Translate GenAI prototypes into production-grade, scalable, and testable services in collaboration with platform and engineering teams. 
  • Work with frontend developers to design agent experiences and contribute to UX interactions with human-in-the-loop feedback. 
  • Stay up to date on trends in LLM architectures, agent frameworks, evaluation strategies, and GenAI standards. 

    • Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 
  • 5+ years of experience in ML/AI engineering, including 2+ years working with transformer models or LLM systems. 
  • Strong knowledge of ML fundamentals, with hands-on experience building and deploying traditional ML models. 
  • Solid programming skills in Python, with experience integrating AI modules into cloud-native microservices. 
  • Experience with LLM frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Haystack), and vector databases (e.g., FAISS, Weaviate, Pinecone). 
  • Familiarity with prompt engineering techniques for system design, memory management, instruction tuning, and tool-use chaining. 
  • Strong understanding of RAG architectures, including semantic chunking, metadata design, and hybrid retrieval. 
  • Hands-on experience with data preprocessing, ETL workflows, and embedding generation. 
  • Proven ability to work with cloud platforms like AWS or Azure for model deployment, data storage, and orchestration. 
  • Excellent collaboration and communication skills, including cross-functional work with product managers, network engineers, and backend teams. 

    • Nice to Have

  • Experience with LLMOps tools, open-source agent frameworks, or orchestration libraries . 
  • Familiarity with Docker, Docker Compose, and container-based development environments. 
  • Background in enterprise networking, SD-WAN, or network observability tools. 
  • Contributions to open-source AI or GenAI libraries.

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    Skills in this job

    Machine Learning Python Docker Aws

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