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Principal Data Scientist-Gen AI, Machine Learning (10042

Job in Toronto, Ontario, C6A, Canada
Listing for: Extreme Networks
Full Time position
Listed on 2026-08-04
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), AI Business & Operations, Data Scientist
Salary/Wage Range or Industry Benchmark: 170000 - 230000 CAD Yearly CAD 170000.00 230000.00 YEAR
Job Description & How to Apply Below
Position: Principal Data Scientist-Gen AI, Machine Learning (10042)

Principal Data Scientist – (Gen AI, Machine Learning)

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, and drive innovation from concept to delivery.

Job Responsibilities
  • Define and drive the long‑term data science and ML strategy, influencing both product direction and organizational priorities
  • Lead high‑impact research initiatives in ML, GenAI, and Graph ML, push the boundaries of applied science, and establish best practices for scalable adoption
  • Partner with engineering and product leadership to align data science innovation with business goals, shaping platform and infrastructure investments
  • Mentor and guide staff‑ and senior‑level scientists, set technical direction, and foster a culture of excellence and innovation
  • Represent the organization externally through publications, talks, and collaborations, strengthening the company’s thought leadership in AI and ML
Requirements
  • Degree in Computer Science, Mathematics, or a related field
  • 8+ years of experience in applied ML research and production deployment
  • 3+ years of hands‑on experience building Generative AI solutions such as RAG, AI Agents, or LLM fine‑tuning in production
  • Experience with Graph ML and Graph technologies such as GNNs or GraphRAG in production
  • Proven track record of end‑to‑end ownership including design, experimentation, validation, deployment, and scaling of ML systems
  • Experience deploying solutions on cloud platforms such as AWS, Azure, or GCP
  • Demonstrated ability to solve highly complex, ambiguous, cross‑domain problems with measurable business impact
Preferred Qualifications
  • MS or PhD in Computer Science, Machine Learning, or a related discipline
  • Experience with distributed Big Data and ML platforms such as Spark, Flink, Kafka, PySpark, or Lakehouse
  • Recognized track record in the ML and AI community through publications, patents, open‑source contributions, or conference talks
  • Strong ability to influence at the organizational level by driving strategy and fostering cross‑functional alignment
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