Principal ML Engineer – eCommerce & Personalization

Position Overview

This role can be remote within the U.S. or Canada, though San Francisco is the preferred location.

At GET (Growth Experience Technology), we’re transforming how customers discover, buy, and use Autodesk. Our mission is to build seamless, data‑informed digital experiences that are intuitive, personalized, and scalable—empowering both our customers and internal teams. We’re investing in smarter platforms, connected sales and marketing systems, and technologies that unlock deeper customer insights and faster decision‑making.

We’re looking for a Principal (Staff) Machine Learning Engineer to help shape the future of Autodesk’s B2C eCommerce platform. This role involves full‑life‑cycle ownership—from ideation and modeling to deployment and optimization. You’ll collaborate across disciplines to develop intelligent systems that personalize user experiences and deliver measurable impact. If you’re passionate about solving ambiguous business problems and building scalable ML systems—even if you don’t meet every qualification—we encourage you to apply.

Guide the design, training, and deployment of ML models for real‑time personalization across Autodesk’s eCommerce ecosystem.

Collaborate with Product Managers and Experience Designers to define what and how personalization should be implemented.

Translate business pain points into scalable ML or analytics solutions.

Work closely with the MLOps team to product ionize models and ensure real‑time inference performance.

Develop experimentation frameworks and run A/B tests to measure impact (e.g., CTR, bounce rate, add‑to‑cart rate).

Build models that scale across product categories, including third‑party integrations for Autodesk’s evolving marketplace.

Promote a data‑informed culture by contributing to initiatives in segmentation, recommendation systems, forecasting, churn prediction, and product analytics.

Mentor and support team members, fostering a collaborative and inclusive environment.

We recognize that talent comes in many forms. If you meet most of the criteria and are excited about the role, we’d love to hear from you.

• Background in Data Science, Statistics, Computer Science, or a related field (we also welcome applicants from non‑traditional DS backgrounds).
• 7+ years of hands‑on related experience. We value experience with machine learning infrastructure, model deployment, optimization and with software design, architecture, and product development.
• Knowledge of data mining, information retrieval, and statistical modeling.
• Exposure to A/B testing and experimental design.
• Experience applying statistical and probabilistic methods to solve real‑world problems; familiarity with financial modeling is a plus.
• Ability to connect data insights to business outcomes.
• Experience in eCommerce, marketing technology, go‑to‑market systems, or other high‑scale data environments (e.g., fintech, social platforms).

• Advanced degree preferred but not required. Equivalent industry experience is highly valued.
• Familiarity with cloud ML platforms (AWS, Azure) and MLOps practices.
• Experience with personalization systems and real‑time inference pipelines.

Work on high‑impact projects that shape the future of digital commerce. Collaborate with a diverse and talented team of engineers, scientists, and product leaders. Enjoy flexible work arrangements and a culture that values innovation, learning, and inclusion.

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting

Salary is one part of Autodesk’s competitive compensation package. For U.S.

-based roles, we expect a starting base salary between $146,900 and $237,600. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

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