Machine Learning Engineer 3D Geometry/ Multi-Modal

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

• 3+ years of machine learning experience

• Experience working in research or experimental environments with evolving requirements

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

• Experience with computational geometry and 3D data (e.g., meshes, B-Rep models)

• Experience working with diverse data representations, including 2D and 3D geometry

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

• Experience using modern AI/GenAI tools in development or experimentation workflows

• Excellent written documentation skills

• Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or related field

• Experience scaling machine learning training and data pipelines (e.g., using Ray or similar frameworks)

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

• Experience with LLMs or generative AI systems (fine-tuning, prompting, evaluation)

• Knowledge of the design, manufacturing, AEC, or media & entertainment industries

• Experience with Autodesk or similar products (CAD, CAE, CAM, etc.)

Salary is one part of Autodesk's competitive compensation package. Offers are based on the candidate's experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

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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 researchers and engineers to build and enable ML-powered capabilities in Autodesk products. You are an ML engineer with strong software engineering skills who is passionate about solving problems and building things, and excited to collaborate with AI researchers to implement generative AI features. You will operate in a fast-moving, research-driven environment where problems are often not fully defined, requiring strong problem framing and rapid iteration.

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

• Build and iterate on ML pipelines, prototypes, and evaluation workflows, enabling rapid deployment and testing of experimental models

• Work with complex datasets and representations for model training, evaluation, and analysis

• Analyze errors and provide solutions to problems

• Present results to collaborators and leadership

The team work in a hybrid working model from our offices in London.

Job Description

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