**Job Requisition ID #**26WD98119****Learn More******About Autodesk**Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.**Salary transparency**Salary is one part of Autodesk’s competitive compensation package. For Canada based roles, we expect a starting base salary between $0 and $0. 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.**Diversity & Belonging** We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here:Please search for open jobs and apply internally (not on this external site).**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 solveproblems that matter.Autodesk is looking for an ML Engineer, ML Systems and Infrastructure to help build the technical foundation behind large-scale machine learning systems. In this role, you will partner with AI researchers, software engineers, and platform teams tobuild scalable pipelines, training infrastructure, data workflows, and production-ready ML systems that support the nextgeneration of AI-powered product experiences.This is an engineering-first role focused on building and operating ML systems at scale. You will work on problems such asdistributed training workflows, data processing pipelines, model evaluation infrastructure, deployment systems, and platform tooling that improves reliability, efficiency, and developer velocity.This role is fully remote-friendly, with team members distributed across the US and Canada.**RESPONSIBILITIES*** 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**MINIMUM QUALIFICATIONS*** 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**PREFERRED QUALIFICATIONS*** 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**THE IDEAL CANDIDATE*** 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#J-18808-Ljbffr