• BSc or MSc in Computer Science, or equivalent industry experience
• 3+ years of experience with data modeling, architecture, and processing skills with varied data representations including 2D and 3D geometry
• The ability to create excellent technical documentation for code, data analysis, and experiment findings
• Experience with software version control, unit tests, and deployment pipelines
• Experience with cloud services & 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 data, Metaflow, Hadoop, Spark, and Hive
• Experience with vector data stores

Desirable

• As a Research Engineer at Autodesk Research, you will work side-by-side with world-class researchers and engineers to build new ML-powered product features that 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 have experience building datasets that combine different data modalities such as text, images, and 3D models. Your skills span across CAD data processing, analysis, indexing, retrieval, and experimentation at multiple scales
• You are excited to collaborate with AI researchers to build datasets that power generative AI features in Autodesk products
• You will report to a research manager in the Autodesk AI Lab
• Own and lead engineering projects in the area of data acquisition, ingestion, and curation
• Organize and curate large, unstructured, disparate multi-modal (text, images, 3D models, code snippets, metadata) data sources into a unified format suitable for machine learning
• Develop and deploy highly scalable distributed systems to process, filter, and deploy datasets for use with machine learning
• Conduct and analyze experiments on data to provide insights
• Produce data visualizations and summaries to communicate data characteristics to researchers and leadership
• Work with our legal and trust teams to ensure compliant and ethical use of data
• Develop and deploy data pipelines into secure remote environments respecting and demonstrating security best practices
• Writing robust, testable code that is well documented and easy to understand