Senior Machine Learning Research Engineer
6 days ago
At Unity, we're driven by a single framework: Empathy, Respect, and Opportunity. We're a collaborative, fast-growing environment where we solve hard problems and enable the success of our community. We're looking for a Senior Machine Learning Research Engineer to join our Ads Applied Research team in driving the overall Ads strategy for our products and services.
In this role, you'll be responsible for guiding and driving the application of machine learning solutions across the organization. Your expertise will help us improve the optimization and machine learning powering our ad networks, marketplaces, and audience tools.
We're looking for a candidate with a PhD in Computer Science, Mathematics, Statistics, or a related field, or equivalent experience in interpreting and translating research to applications. You should have experience in successfully taking research and turning it into concrete product innovations with impact.
Your expertise in modeling frameworks (Tensorflow, PyTorch) and understanding of model architectures and mechanisms will be crucial in explaining machine learning and interpreting modeling efficacy for further improvements. You should also be capable of conducting analysis, statistics, and data literacy to deduct where the challenges and opportunities lie.
Key Responsibilities:
- Define and execute advanced machine learning models and algorithms to help translate complex business problems.
- Be at the forefront of the latest machine learning research to improve our Ad platform Machine Learning capabilities.
- Optimize, improve, and innovate ML practices to establish us as an industry leader.
- Form and validate hypotheses on new aspects of modeling and potency of new datasets for ML.
- Drive 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.
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