Principal Applied Research Machine Learning Engineer

2 weeks ago


Copenhagen, Copenhagen, Denmark Unity Full time

The Opportunity

At Unity, we're driven by a framework of Empathy, Respect, and Opportunity. In a collaborative, fast-growing environment, we're solving complex problems and enabling the success of our community. As a member of the Unity Ads Applied Research team, you'll have the chance to make a meaningful impact.

We're seeking a talented machine learning expert to drive our applied research and analysis on how to improve the optimization and machine learning powering our ad networks, market place, and audience tools. In this role, you'll be responsible for defining and executing advanced machine learning models and algorithms to help translate complex business problems.

What You'll Be Doing

As a machine learning and data science expert, you'll guide and drive the application of machine learning solutions across the organization. Your responsibilities will include:

  • Defining and executing advanced machine learning models and algorithms to help translate complex business problems
  • Staying at the forefront of the latest machine learning research to improve Unity's Ad platform Machine Learning capabilities
  • Optimizing, improving, and innovating ML practices to establish Unity as an industry leader
  • Forming and validating hypotheses on new aspects of modeling and potency of new datasets for ML
  • Driving optimization hypotheses by analyzing the drivers for impactful machine learning and arguing the hypotheses and success for the next steps of development
  • Making requirements and communicating data and machine learning capability needs to the product and engineering teams as the authority in Data for ML
  • Driving the overall direction of the machine learning future for Ads to support strategic goals and vision

What We're Looking For

We're looking for a candidate with experience in guiding machine learning development via revolutionary steps to keep Unity Ads at the forefront of ML performance. The ideal candidate will have a PhD in Computer Science, Mathematics, Statistics, or a related technical field, or equivalent experience in interpreting and translating research to applications. Additionally, they should have experience successfully taking research and turning it into concrete product innovations with impact.

The successful candidate will have expertise with modeling frameworks (Tensorflow, PyTroch) and understanding of model architectures and mechanisms. They should also be able to explain machine learning and interpret the modeling efficacy for further improvements. Finally, they should be capable of conducting analysis, statistics, and data literacy to deduct where the challenges and opportunities lie.



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