Machine Learning Engineer, ML Systems and Infrastructure

Position Overview

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter.

This role is fully remote-friendly, with team members distributed across the US and Canada.

• Build and maintain components of ML pipelines for data preparation, model training, evaluation, deployment, and monitoring.
• Develop reliable software and infrastructure that supports scalable machine learning workflows.
• Contribute to distributed data processing and training systems used by researchers and engineering teams.
• Support data ingestion, transformation, validation, and serving for large‑scale structured and semi‑structured technical datasets.
• Improve automation, testing, CI/CD, observability, and operational reliability for ML systems.
• Troubleshoot data, infrastructure, and performance issues in collaboration with senior engineers.
• Participate in design discussions and contribute ideas that improve system scalability, maintainability, and efficiency.
• Document technical decisions, workflows, and operational processes clearly.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent industry experience.
• At least 2 years of industry experience in software engineering, machine learning infrastructure, distributed systems, data platforms, or related areas.
• Strong software engineering fundamentals, including coding, testing, debugging, and code quality.
• Proficiency in Python and experience building production‑quality software.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with containers, version control, CI/CD, and modern development workflows.
• Experience working with data‑intensive systems, backend systems, or ML pipelines.
• Ability to work independently on well‑defined problems with moderate ambiguity.

• Experience building data pipelines for large‑scale structured and semi‑structured technical datasets.
• Familiarity with data lineage, provenance, governance, and responsible data usage in ML systems.
• Familiarity with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms.
• Familiarity with model deployment, inference services, monitoring, and observability for production ML systems.
• Familiarity with ML‑ready representations for geometry, graph, hierarchical, or multimodal data.
• Experience working with CAD, BIM, AEC, or other complex domain‑specific data formats.

• Is a strong software engineer with interest in machine learning systems.
• Enjoys improving reliability, automation, and operational excellence.
• Communicates clearly and collaborates well across functions.
• Learns quickly and thrives in a fast‑moving environment.
• Brings sound judgment, curiosity, and ownership to engineering work.

For Canada‑based roles, the starting base salary is expected to be between $0 and $0. Offers are based on candidate experience and geographic location and may exceed this range. The compensation package may include annual cash bonuses, stock grants, and a comprehensive benefits package.

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more at