Principal/Staff Machine Learning Engineer/Data Scientist

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 fuel sustainable growth by rethinking how customers discover, buy, and use Autodesk. Our focus is creating a seamless, data-driven experience that feels simple, predictable, and tailored to customer needs—while also making it easier and more efficient for our teams to support them.  
To get there, we're building smarter digital experiences, strengthening our platforms, and making our sales and marketing efforts much more efficient and connected. While the product experience will play a key role, a real unlock will come from the technologies that power better customer insights, more personalized engagement, and faster sales cycles.  

Our GET Machine Learning Engineering org is looking for a seasoned Staff level Data Scientist/Machine Learning Engineer to drive data-informed decisions for Autodesk B2C business. You will play a critical role in helping Autodesk build the eCommerce platforms of the future.  

Data Scientists/MLE are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms. Unlike other companies that separate these roles, our Data Scientists work on projects from ideation to implementation.  

As a Staff Data Scientist at Autodesk, you will be responsible for the development and training of cutting-edge machine learning models and algorithms that can effectively leverage our users’ platform activities and industry trends to create personalized recommendations that are delivered to our users at the optimal moment. 

Responsibilities 

• Act as a Champion for a data-driven culture, evangelizing best practices and shape the direction of key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights.  

• Expand ML Capabilities – Identify, design, prototype, and build scalable end-to-end ML pipelines that enhance Autodesk’s eCommerce personalization at scale.  

• Drive Experimentation at Scale – Develop and implement robust experimentation frameworks to increase velocity while maintaining scientific rigor, enabling rapid iteration and deployment of personalization models.  

• Craft compelling Stories and make logical recommendations based on insights of data and ML models. 

• Partner with cross-functional teams to initiate, lead and drive to completion large-scale/complex strategic projects for teams, departments and the company. 

• Act as a thought partner to senior cross-functional leaders to prioritize/scope projects, provide recommendations, and evangelize data-driven business decisions in support of strategic goals.  

• Mentor and guide junior data scientists/MLE by helping with project planning, technical decisions, and code and document review.  

Minimum Qualifications 

• Bachelor's degree in data science, statistics, computer science, a related technical field 

• 7 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). 

• 5 years of experience with design and architecture; and testing/launching software products. 

• 7+ 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. 

Preferred Qualifications 

• MS or PhD in a quantitative discipline: data science, statistics, computer science, a related technical field. 

• 10+ 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