Machine Learning Cloud Optimization Engineer Remote or Hybrid  

Machine Learning Cloud Optimization Engineer  

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. As a 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.  

You will report to a research manager in the Research Engineering organization of Autodesk Research. 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 

• Profile and optimize machine learning tasks and code 

• Write efficient code for machine learning tasks, focusing on software rather than hardware 

• Understanding of AWS Cloud, Kubernetes and Ray Framework 

• Prepare appropriate containers and instances for various machine learning tasks 

• Train and optimize machine learning models 

• Collaborate on projects at the intersection of research and product with a diverse, global team of researchers and engineers 

• Support research through the construction of ML pipelines, prototypes, and reusable, testable code 

• Process data and analyze feature extractions 

• Analyze errors and provide solutions to problems 

• Present results to collaborators and leadership 

Minimum Qualifications 

• BSc or MSc in Computer Science, or equivalent industry experience 

• 3+ years of software development experience 

• Experience with version control, reproducibility, and deploying machine learning models 

• Experience with cloud services and architectures (e.g. AWS, Azure) 

• Proficiency with modern deep learning libraries and frameworks (PyTorch, Lightning, Ray) 

• Excellent written documentation skills to document code, architectures, and experiments 

Preferred Qualifications 

• Experience with data modeling, architecture, and processing using varied data representations including 2D and 3D geometry  

• Experience with adding computational graph support, runtime or device backend to Machine learning libraries (PyTorch or Lightning Ray) support.  

• 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.)