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 to solve problems that matter.
As a Software Engineer at Autodesk Research, you will be working side-by-side with world-class researchers and engineers to build new ML-powered product features that will 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 scalable data pipelines to aggregate, prepare, and process data for use with machine learning.
Your skills span across data processing and distributed systems with a strong software engineering base. You are excited to collaborate with AI researchers to build state-of-the-art generative AI features in Autodesk products.
You are a good communicator and comfortable working at the intersection of research & product.
Location : 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.
Responsibilities
Collaborate on engineering projects for product with a diverse, global team of researchers and engineers
Develop and deploy highly scalable distributed systems to process, filter, and deploy datasets for use with machine learning
Process large, unstructured, disparate multi-modal (text, images, 3D models, code snippets, metadata) data sources into formats suitable for 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
Analyze errors and provide solutions to problems that arise
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
Experience with cloud services & architectures (AWS, Azure, etc.)
Excellent written communication skills to document code, architectures, and experiments
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, or Hive
Experience with vector data stores
Proficiency with Linux systems and bash terminals
Knowledge of cloud architectures and networking
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 searchable CAD databases
Knowledge of statistics
Ability to analyze data and communicate results effectively using tools such as Pandas, Matplotlib, Seaborn, Plotly, R or others
Knowledge of the design, manufacturing, AEC, or media & entertainment industries
Experience with Autodesk or similar products (CAD, CAE, CAM, etc.)
The Ideal Candidate
A self-starter with initiative to search for solutions and execute on problems with minimal supervision
Comfortable building prototypes from scratch as well as writing maintainable code within existing codebases
A curious, creative problem-solver who is excited to learn & develop new technologies
A fast learner & excellent communicator who can effectively collaborate across global locations
Comfortable working in newly forming ambiguous areas where learning and adaptability are key skills
Takes a great satisfaction in building scalable and maintainable systems that will be relied on by others