Principal Machine Learning Engineer, 3D
4 weeks ago
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.
As a Principal Machine Learning Engineer at Autodesk Research, you will work side-by-side with world-class researchers and engineers to build new ML-powered product features to help our customers imagine, design, and make a better world.
You are a software engineer who is passionate about solving problems and building things. You are excited to collaborate with AI researchers to implement generative AI features in Autodesk products.
We are a global team, located in London, San Francisco, Toronto, and remotely. For this role, we support both in-person, hybrid, and remote work.
Responsibilities
Collaborate on projects at the intersection of research and product with a diverse, global team of researchers and engineers
Develop new or improve existing ML models used in CAD software
Process data and analyze feature extractions
Design solutions based on error analysis
Present results to collaborators and leadership
Review relevant AI/ML literature to identify emerging methods, technologies, and best practices
Requirements
BSc or MSc in Computer Science, or equivalent industry experience
3+ years of software development experience
Proficiency with modern deep learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.) as well as frameworks (e.g. PyTorch, Lightning, Ray etc.)
Experience with deploying machine learning models in production settings
Experience with version control, reproducibility, and writing reusable, testable code
Experience with data modeling, architecture, and processing using varied data representations including 2D and 3D geometry
Experience with cloud services and architectures (e.g. AWS, Azure)
Excellent written documentation skills to document code, architectures, and experiments
Preferred Qualifications
Experience scaling ML training and data pipelines
Experience working with distributed systems
Knowledge of the design, manufacturing, AEC, or media & entertainment industries
Experience with Autodesk or similar products (CAD, CAE, CAM, etc.)
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