Job Title

Machine Learning Engineer: 2D & 3D Geometric Data, Generative AI. Remote or Hybrid Canada Position Overview Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. We''re enhancing our applications with cloud- native capabilities, including data at scale, edge computing, AI-based solutions, and advanced 3D modeling and graphics. This innovation is happening across our flagship productsAutoCAD, Revit, and Construction Cloudand Forma, our new Industry Cloud. As a Machine Learning Engineer on the AEC Solutions team, you will join a team of technologists to help build foundation models and generative AI tools for the AEC industry. You will work collaboratively to create and interpret design data that can enhance design and engineering workflows. Report: You will report to the Machine Learning Manager in the Architecture, Engineering, and Construction (AEC) Solutions Team. Location: We support hybrid work or remote work in Canada. Responsibilities Collaborate with other engineers to develop scalable data pipelines and architectures Work with large-scale datasets including text and geometric data, to support preprocessing, augmentation, analysis and content understanding Write production-quality code for model training, testing, and deployment. Design and execute model experiments, evaluate performance, and iterate based on findings Monitor, troubleshoot, and optimize machine learning models to ensure accuracy, efficiency, and low latency Perform requirements analysis, working with team members of different levels and documenting solutions Communicate your findings through quantitative data analysis and qualitative visuals and insights Implement agile approaches ensuring flexibility and responsiveness to evolving project needs Minimum Qualifications Bachelors or Masters degree in Computer Science, Machine Learning , Artificial Intelligence, Mathematics, Statistics, or a related technical field, or equivalent industry experience 35+ years of hands-on experience in machine learning engineering or a closely related field Expertise in training deep neural networks (e.g., CNNs, Transformers), with proficiency in modern deep learning libraries and frameworks such as PyTorch , Lightning, and Ray Proven experience scaling machine learning training and data pipelines Hands-on experience with Large Language Models (LLMs) and related technologies, including embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems Strong background in computational geometry and geometric methods, including mesh or B-Rep models Experience in data modeling, architecture, and processing using varied data types, particularly 2D and 3D geometric data representations Proficiency with version control, model reproducibility practices, and deployment of machine learning models Familiarity with cloud services and architectures, especially AWS (e.g., SageMaker Studio), and ideally Azure Strong understanding of fundamental computer science algorithms and their scaling behaviors Excellent programming skills in both procedural and data-analytics-oriented languages (e.g., Python) Ability to translate theoretical machine learning concepts into practical, scalable solutions and prototype implementations Excellent documentation skills, including code, architecture design, and experiment tracking Practical experience with hyperparameter tuning, model optimization methods, and acceleration techniques Experience with distributed computing platforms such as Apache Spark or Hadoop Demonstrated experience developing high-scale, production-grade machine learning algorithms Preferred Qualifications Experience building or working with distributed systems Background in the Architecture, Engineering, or Construction (AEC) industry Domain knowledge in design, manufacturing, AEC, or media & entertainment industries Experience with Autodesk products or similar software tools ______________________________________________________________________________________________________________ Qualifications minimales 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 our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers. When youre an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us! Salary transparency / Transparence salariale Salary is one part of Autodesks competitive compensation package. Offers are based on the candidates experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package. Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). About the company Autodesk, Inc. is an American multinational software corporation that makes software services for the architecture, engineering, construction, manufacturing, media, education, and entertainment industries. Notice Talentify is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Talentify provides reasonable accommodations to qualified applicants with disabilities, including disabled veterans. Request assistance at or 407-000-0000. Federal law requires every new hire to complete Form I-9 and present proof of identity and U.S. work eligibility. An Automated Employment Decision Tool (AEDT) will score your job-related skills and responses. Bias-audit & data-use details: . NYC applicants may request an alternative process or accommodation at or 407-000-0000. #J-18808-Ljbffr