Principal Machine Learning Engineer US or Canada Hybrid or Remote

Job Requisition ID #

About the Growth Experience Technology Machine Learning Team (GET-ML)

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, in a role 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 Machine Learning. 

Our 2025 focus is on the Autodesk Commerce & Support  Assistant, an LLM-driven, Universal Chatbot intended to provide generative answers to a wide range of our customers’ inquiries. This system is in production and already driving rich customer conversations and better outcomes. Other examples of our work include models for routing customer queries to AI agents, and measuring the impact of automation on customer forums.

Position Overview

As a Principal ML Engineer on the team, you will be responsible for the design, analysis, and delivery of data-driven solutions to significant business challenges. Principal MLEs operate at a programmatic scale, taking responsibility for significant technical solutions and coordinating delivery with multiple stakeholder teams. As the role develops, Principal MLEs have the opportunity to become the key technical experts for important aspects of some of our most impactful systems.

Our team culture focuses on collaboration, mutual support, and continuous learning. As a Principal MLE, the role will include providing technical guidance, and other relevant advice to peers and colleagues within the team, and across the company. We emphasize agile, hands-on, and technical approach at all levels of the team.

Finally, as a team we strive for excellence in the theory and practice of Machine Learning. This means that we want to continuously improve our method of doing Machine Learning, as well as our knowledge of trends and techniques relevant to our areas. We encourage personal development and knowledge sharing.

Location: United States or Canada Hybrid or Remote Office

Responsibilities

• Design & Implement Machine Learning capabilities that improve Autodesk’s eCommerce & Customer platforms, especially the Commerce & Support Assistant (agentic chatbot)

• Develop a programme of work, coordinating with partners and stakeholders, to solve strategic business objectives

• Collaborate to translate business requirements and objectives into problems that can be solved with a combination of data, statistics, and machine learning

• Perform statistical and data analysis and exploration to generate datasets for model training, as well as insights for design of solutions in the above areas

• Collaborate with other members of the team to get to better solutions, to improve our processes, and to keep our team at the cutting edge of technology

• Lead, mentor and support more junior members of the team in achieving DS & ML excellence

Minimum Qualifications

• MS or PhD in Computer Science, Statistics, Engineering, Economics, or related field We also welcome applicants from non-traditional DS backgrounds

• 5+ years of applicable work experience

• Knowledge of experimental design and analysis of results

• Demonstrable experience with applying Machine Learning, including both Deep Learning (PyTorch) and Classical ML (Scikit-Learn)

• Demonstrable Experience in production with Large Language Models, especially in the context of interactive dialog systems and chatbots (RAG, Generative AI, Conversational Agents)

• An ability to work with cross-functional teams and manage stakeholders

• Familiarity with Fine-tuning Large Language Models, especially in the context of interactive dialog systems and chatbots (RAG, Generative AI, Conversational Agents, AI agent orchestration)

• SQL and experience with big data technology such as Hive, Presto, Glue, (Py)Spark, or Athena

• Proficiency with the Python Data Science stack, e.g. Pandas, etc

• Experience from deploying systems that use NLP such as Information Retrieval (IR), Recommender Systems (RecSys), or other NLP Applications

• Experience working in cross-functional teams to deliver ML solutions at scale

• Advanced software engineering skills including data structures and algorithms

• Experience with data pipelines and model serving in AW