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Engineering

Machine Learning Research Engineer - New Grad

San Francisco, California
Full-time
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About Us:
At Scale, our mission is to accelerate the development of Machine Learning and AI applications across multiple markets. Our first product is a suite of APIs that allow AI teams to generate high-quality ground truth data. Our customers include OpenAI, Zoox, Lyft, Pinterest, Airbnb, nuTonomy, and many more.

Scale AI is an equal opportunity employer. We aim for every person at Scale to feel like they matter, belong, and can be their authentic selves so they can do their best work. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Scale AI is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

The goal of the ML team at Scale is to develop machine learning solutions advancing the company mission. Our current focus areas are Computer Vision ( 2D/3D detection, 2D/3D segmentation, object tracking), Machine Learning (e.g. semi-supervised learning, active learning) and Natural Language Processing.

We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. We currently complete millions of tasks a month, and will grow to complete billions of tasks monthly.

As a Machine Learning Research Engineer - New Grad, you will:

  • Research and develop machine learning solutions to assist humans in the loop.
  • Aid in the creation of high quality ground truth data with speed and accuracy.
  • Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
  • Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics
  • Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
  • Work with massive datasets to develop both generic models as well as fine tune models for specific products

Requirements:

  • Graduating in 2021 from a PhD or MS Program with a focus on Machine Learning, Deep Learning, Computer Vision or Natural Language Processing or pursing an undergrad degree and have published papers in Machine Learning fields
  • Have had a previous internship around Machine Learning, Deep Learning, Computer Vision or Natural Language Processing

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