Autodesk
Overview
Machine Learning Engineer at Autodesk. 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. The location of this role is flexible. We are a global team, located in London, San Francisco, Toronto, and remotely. Autodesk is a flexible hybrid-first company, allowing workers to work remotely, in an office, or a mix of both. The position includes working as a Research Engineer at Autodesk Research, collaborating with world-class researchers and engineers to build new ML-powered product features that help customers imagine, design, and make a better world. You are a software engineer who is passionate about solving problems and building things, with experience in building datasets that combine data modalities such as text, images, and 3D models. Your experience spans CAD data processing, analysis, indexing, retrieval, and experimentation at multiple scales, and you will collaborate with AI researchers to power generative AI features in Autodesk products. You should be a good communicator and comfortable operating at the intersection of research and product. Responsibilities
Own and lead engineering projects in the area of data acquisition, ingestion, and curation Organize and curate large, unstructured, disparate multi-modal data sources (text, images, 3D models, video) into a unified format for machine learning Develop and deploy highly scalable distributed systems to process, filter, and deploy datasets for ML use Conduct and analyze experiments on data to provide insights Write robust, testable code that is well documented and easy to understand Serve as an analytical advisor applying best practices and understanding the theories in the discipline Possibly lead projects or key elements within broader projects and improve ongoing processes Build effective relationships with senior practitioners and peers; develop a network of external peers Work independently with guidance at critical points; may mentor colleagues Minimum Qualifications
BSc or MSc in Computer Science or equivalent industry experience Experience with software version control, unit tests, and deployment pipelines Strong data modelling, architecture, and processing skills with varied data representations including 2D and 3D geometry Excellent written communication skills to document code, data analysis, and experimental findings Experience with cloud services and architectures (AWS, Azure, etc.) Experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra) Experience with frameworks such as Ray, Metaflow, Hadoop, Spark, and Hive Experience with implementing ML models Experience working with large data lakes and data streams Proficiency with Linux systems and bash terminals Preferred Qualifications
Experience with computational geometry such as mesh or boundary representation data processing Experience with CAD model search and retrieval in PLM systems or other CAD databases Knowledge of design, manufacturing, AEC, or media & entertainment industries Knowledge of statistics Ability to analyze data and communicate results using tools such as Pandas, Matplotlib, Seaborn, Plotly, R Experience with open-source pre-trained language and vision models such as BERT, LLaMA, LLaVA, etc. Experience with NLP tools such as Spacy, NLTK, Gensim Experience creating large-scale datasets and benchmarks Proficiency in software engineering and cloud-based systems to deliver data pipelines to ML projects The Ideal Candidate
Team player with curiosity Ability to handle domain-specific file formats and connect information across sources to provide new ML features Self-drive and creativity to deliver scalable data pipelines for ML projects About Autodesk
Autodesk creates software that helps turn ideas into reality—whether in buildings, cars, factories, or movies. We value culture, collaboration, and belonging, guiding how we work with customers and partners. Benefits
Autodesk offers health and financial benefits, time away, and wellness programs. Learn more about benefits in the U.S. at the Autodesk benefits site. Salary transparency
For U.S.-based roles, starting base salary ranges from $119,800 to $206,690, with compensation potentially including bonuses, stock grants, and a comprehensive benefits package. Equal Employment Opportunity
Autodesk is an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider applicants with criminal histories where permitted by law. Diversity & Belonging
Autodesk fosters a culture of belonging where everyone can thrive. Learn more at our diversity and belonging page. Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site).
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Machine Learning Engineer at Autodesk. 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. The location of this role is flexible. We are a global team, located in London, San Francisco, Toronto, and remotely. Autodesk is a flexible hybrid-first company, allowing workers to work remotely, in an office, or a mix of both. The position includes working as a Research Engineer at Autodesk Research, collaborating with world-class researchers and engineers to build new ML-powered product features that help customers imagine, design, and make a better world. You are a software engineer who is passionate about solving problems and building things, with experience in building datasets that combine data modalities such as text, images, and 3D models. Your experience spans CAD data processing, analysis, indexing, retrieval, and experimentation at multiple scales, and you will collaborate with AI researchers to power generative AI features in Autodesk products. You should be a good communicator and comfortable operating at the intersection of research and product. Responsibilities
Own and lead engineering projects in the area of data acquisition, ingestion, and curation Organize and curate large, unstructured, disparate multi-modal data sources (text, images, 3D models, video) into a unified format for machine learning Develop and deploy highly scalable distributed systems to process, filter, and deploy datasets for ML use Conduct and analyze experiments on data to provide insights Write robust, testable code that is well documented and easy to understand Serve as an analytical advisor applying best practices and understanding the theories in the discipline Possibly lead projects or key elements within broader projects and improve ongoing processes Build effective relationships with senior practitioners and peers; develop a network of external peers Work independently with guidance at critical points; may mentor colleagues Minimum Qualifications
BSc or MSc in Computer Science or equivalent industry experience Experience with software version control, unit tests, and deployment pipelines Strong data modelling, architecture, and processing skills with varied data representations including 2D and 3D geometry Excellent written communication skills to document code, data analysis, and experimental findings Experience with cloud services and architectures (AWS, Azure, etc.) Experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra) Experience with frameworks such as Ray, Metaflow, Hadoop, Spark, and Hive Experience with implementing ML models Experience working with large data lakes and data streams Proficiency with Linux systems and bash terminals Preferred Qualifications
Experience with computational geometry such as mesh or boundary representation data processing Experience with CAD model search and retrieval in PLM systems or other CAD databases Knowledge of design, manufacturing, AEC, or media & entertainment industries Knowledge of statistics Ability to analyze data and communicate results using tools such as Pandas, Matplotlib, Seaborn, Plotly, R Experience with open-source pre-trained language and vision models such as BERT, LLaMA, LLaVA, etc. Experience with NLP tools such as Spacy, NLTK, Gensim Experience creating large-scale datasets and benchmarks Proficiency in software engineering and cloud-based systems to deliver data pipelines to ML projects The Ideal Candidate
Team player with curiosity Ability to handle domain-specific file formats and connect information across sources to provide new ML features Self-drive and creativity to deliver scalable data pipelines for ML projects About Autodesk
Autodesk creates software that helps turn ideas into reality—whether in buildings, cars, factories, or movies. We value culture, collaboration, and belonging, guiding how we work with customers and partners. Benefits
Autodesk offers health and financial benefits, time away, and wellness programs. Learn more about benefits in the U.S. at the Autodesk benefits site. Salary transparency
For U.S.-based roles, starting base salary ranges from $119,800 to $206,690, with compensation potentially including bonuses, stock grants, and a comprehensive benefits package. Equal Employment Opportunity
Autodesk is an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider applicants with criminal histories where permitted by law. Diversity & Belonging
Autodesk fosters a culture of belonging where everyone can thrive. Learn more at our diversity and belonging page. Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site).
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