Machine Learning Engineer, Computer Vision

Usertesting, as the world's leading User Experience Research provider, has an enormous repository of rich, multi-modal data, with millions of video, audio, and text documents around real users engaging with digital design.

Our team of data engineers and scientists is focused on creating a competitive advantage for UserTesting and our customers through novel data infrastructure, metrics, insights and data services. We are a small but rapidly growing team that builds and leverages state-of-the-art Machine Learning (ML) systems, leveraging computer vision and natural language processing to understand how design choices affect user experiences.

We are looking for ML experts with strong fundamentals in software development and computer science. You will be working in a fast-paced environment, working across teams and organizations, and should be comfortable with a rough first-pass solution in order to accelerate learning before bringing out the big Deep Learning guns. 

At UserTesting, we love building elegant user experiences, with a passion for the customer experience and deeply understanding our users. You will apply your knowledge of ML for development of key features to accelerate our customers’ ability to understand and analyze vast amounts of rich, multi-modal data. In addition to green-field research and development, you will be excited to be developing new features, maintaining existing code, fixing bugs, and contributing to overall system design.

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Responsibilities
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  • Design, build, develop, validate, productionise, monitor, and maintain ML models
  • Work across product teams to identify opportunities for data-driven features and translate them into actionable data science projects
  • Be an in-house ML expert, lead ML initiatives, and help cultivate company-wide best practices for ML
  • Work with data engineers to design data pipelines to effectively store, normalize, and access multi-modal data
  • Be a part of an engineering team with total responsibility of both algorithms, modeling, engineering and production scaling and support 

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Requirements
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  • Advanced Degree preferred (MS or PhD) in computer science, machine learning, statistics, or a closely related field
  • 3+ years industry experience in building and productionising machine learning systems, especially those powered by deep neural networks
  • 3+ years of programming experience, proficiency in Python, Java, Scala or C++
  • Experience with open source machine learning toolkits: Tensorflow, Keras, Theano, CNTK, Scikit-learn, OpenCV, Pandas, Numpy, LibSVM

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