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AutodeskPosted 1 week ago

Senior Principal AI/ML Developer

$178,875–$178,875 year

RemoteCalifornia, United States

Full TimeSenior LevelBachelors DegreeEnterprise

Job Summary

Develop and train cutting-edge machine learning models to create personalized recommendations for Autodesk's eCommerce platforms, leveraging user platform activities and industry trends. Design and build scalable end-to-end ML pipelines that enhance personalization at scale, while implementing robust experimentation frameworks to increase deployment velocity. Act as a champion for a data-driven culture by evangelizing best practices across segmentation, recommendation systems, forecasting, product analytics, churn prediction, and insights. Partner with cross-functional teams to lead large-scale strategic projects and serve as a thought partner to senior leaders in prioritizing initiatives and driving data-informed business decisions. Mentor junior data scientists and machine learning engineers on project planning, technical decisions, and code reviews.

Required Qualifications

  • Bachelor's degree in data science, statistics, computer science, a related technical field
  • 10 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)
  • 7 years of experience with design and architecture; and testing/launching software products
  • 10+ years of hands-on experience with data mining, and information retrieval
  • Experience in A/B testing and experimental design
  • Strong understanding of statistics, probability, and financial modeling
  • Ability to translate data insights into business impact

Desired Qualifications

  • MS or PhD in a quantitative discipline: data science, statistics, computer science, a related technical field
  • 15+ years of hands-on experience in machine learning design, development and deployment, ideally in eCommerce domain
  • Hands-on experience with cloud machine learning platform (AWS, Azure) and MLOps best practices

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