Intern, Machine Learning Operations Engineer

Job Requisition ID #

25WD92313

25WD92313, Intern, Machine Learning Operations Engineer

French translation to follow!/Traduction française à suivre!

About the GET-ML team

The GET-ML Team is responsible for delivering Machine Learning features that transform the customer experience for Sales, Marketing, and Customer Success functions at Autodesk.

We aim to help our customers, through conversation, personalization, and other intelligent features on our platform. Our team members work extensively with stakeholders across the company, with significant technology leadership and opportunity for impact. We work in a supportive and collaborative way, applying the latest technology and rigorous analysis to solve complex customer problems using ML.

Our current focus is on the Commerce & Support Assistant and Personalization for eCommerce. All our systems are in production and create better outcomes for our customers.

At Autodesk, we're reimagining what's possible. As a global leader in 3D design, engineering, and entertainment software, we help people everywhere imagine, design, and create a better world.

Position Overview

The ML Ops Engineering team is a fast-moving team combining software engineering with ML system deployment and operations. As an ML Ops Engineer on the team, you will be responsible for automating and simplifying machine learning workflows and deployments. ML Ops Engineers work to implement and deliver ML capabilities to solve complex real-world problems and deliver value to our customers. These processes include model development, testing, integration, release, and infrastructure management.

Our team culture is built on collaboration, mutual support, and continuous learning. In this role, you will automate and standardize processes across the ML lifecycle, collaborating with ML Engineers, Software Engineers, and other cross-functional stakeholders. We emphasize an agile, hands-on, and technical approach at all levels of the team. As a group, we want to continuously improve our work and knowledge of trends and techniques relevant to our areas.

We strive for excellence and pursue it with personal development and knowledge sharing.

The 2026 Canada Internship program runs for 16 weeks (May 4th – August 21st, 2026). All internships are paid. As an intern, you will contribute to meaningful projects, be mentored by industry leaders, and participate in tech talks and other activities designed to support your personal and professional development. Our internships align with Autodesk’s Flexible Workplace approach, which is designed to meet the needs of our business while providing flexibility in support of office, remote and hybrid work preferences.

Responsibilities

• Deploy ML models as part of a streamlined end-to-end, continuous, and automated process, at scale
• Design and implement services, tests, and interfaces to monitor and evaluate Machine Learning capabilities that improve Autodesk’s eCommerce platform
• Design and implement data pipelines and automated workflows to operationalize data at different stages of the Machine Learning lifecycle
• Collaborate with other members of the team in reaching better solutions, and to position our team at the cutting edge of technology and ML practice
• Deploy innovative solutions from non-production environments to production with an eye on scalability and observability

Minimum Qualifications

• BS or MS in Computer Science, Statistics, Engineering, Economics, or related field We also welcome applicants from non-traditional ML backgrounds
• 0-3 years of applicable work experience in Software Engineering or Data Engineering or ML Engineering
• Demonstrated expertise with applying Machine Learning

Preferred Qualifications

• Familiarity with Large Language Models and their applications e.g. RAG, Generative AI Agents
• Experience in the eCommerce domain or with Personalization of any form
• Experience with data engineering platforms such as Hive, Presto, Glue, (Py)Spark, or Athena
• Experience with ML deployment frameworks like Metaflow and the AWS ML ecosystem
• Strong Software Engineering skills

The Ideal Candidate

There is no single ideal profile for a candidate for this role. We encourage you to apply if you think you would add to our team’s ability to deliver innovative ML, even if you don’t meet every single criterion.