
Intern, Data Science (Autodesk Construction Cloud)
Internship On Site (Internship) @Autodesk posted 7 months ago in Data ScienceJob Description
Position Overview
Autodesk and Autodesk Construction Cloud makes software for people who make things. If you’ve ever driven a high-performance car, admired a towering skyscraper, used a smartphone, or watched great science fiction films, chances are you’ve experienced what millions of Autodesk customers are doing with our software.
The Autodesk Construction Cloud Intelligence Team is looking for a driven and naturally curious data science intern who can hit the ground running in a fast paced, complex environment. You will work with the team to develop and deliver new cutting-edge computer vision and natural language processing solutions that serve as the foundation of current and future Autodesk Construction Cloud products. Past projects include, for example, construction photo understanding and/or building documents information extraction and matching
You will… (Responsibilities):
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Use data science, computer vision, and natural language processing to improve product development, customer success, content understanding across our construction cloud product.
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R&D to solve construction project using computer vision & natural language processing
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Collaborate with other data scientists and engineers developing and deploying ML algorithms
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Document and communicate your findings through quantitative data analysis
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Present progress to stakeholders
Who you are… (Requirements):
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Full-time student pursuing a BS, MS, or PhD in Computer Science, or equivalent
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Proficient in Python
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Proficient in TensorFlow or PyTorch (or another standard deep learning framework)
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Proficient in deep learning, computer vision, and/or natural language processing
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Experience in AWS environment
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Experience completing multiple data science projects end-to-end; from idea generation, goals formulation, to implementation and deliverables
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Comfortable communicating data and results, both verbally and visually
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Bonus: Experience with top-tier publications in machine learning domains (e.g., CVPR, ICCV, PAMI, ICML, JMLR, ACL, EMNLP, etc.)