Intern, Data Acquisition and ML Research

Key Skills

C Programming, C++, Cloud computing, Data science techniques, Java Programming, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

As an Intern at Autodesk Research you'll apply your skills with data engineering to help our customers design and create a better, safer, more sustainable world. We are a team of researchers, engineers, and industry domain experts working on projects that include learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.

We have an opening for an intern who will prepare data processing pipelines for machine learning research as part of a team developing ML to enable design exploration (getting to alternative design solutions), design automation (getting to the finished design faster), and sustainable design (with less negative impact).

You will work closely with members of Autodesk's AI Lab to design scalable data pipelines that can process design data for use with machine learning. The AI Lab collaborates with top academic & industry labs, combining the best of an academic environment with product-driven research.

Possible Locations

San Francisco, US

Minimum Qualifications

• Full-time student pursuing a Bachelor or Master degree in Computer Science, Data Science, Computational Design, Machine Learning, or a related discipline in an accredited program with at least one academic term to complete post-internship
• Broad understanding of data engineering and feature extraction for machine learning and deep learning
• Excellent programming and software development skills in Python including writing unit tests
• Proficient with machine learning frameworks and data structures ideally including pyTorch and numpy
• Familiar with parallel data processing both locally and in the cloud
• An excellent communicator and team player
• Interest or experience in design (e.g., industrial or mechanical design)

Preferred Qualifications

• Expertise with scaling data processing pipelines using AWS
• Experience writing pyTorch dataloaders and manipulating pyTorch tensors and numpy arrays
• Knowledge of 3D computer graphics, computational geometry, and 3D geometry manipulation
• Experience with CAD programs