Role OverviewThe Brand Ads Team builds technologies that unlock business growth potential. This team owns several ads products: reservation ads, auction ads, and innovative content ads that enables advertisers and users to foster more awareness of their brand to attain their business goals. We work on the end-to-end ads delivery tech stack, including ads bidding, ranking, and forecasting.
What You Will Do
As a Machine Learning Engineer on the Brand Ads team, you will work on real-world problems such as forecasting available inventory, optimizing auction traffic, and using machine learning to improve delivery quality and efficiency.
Why It Might Be a Fit
Successful candidates must be able to commit to an onboarding date by the end of the year. You will collaborate closely with engineers, product managers, data scientists, and strategy partners to turn ambiguous business challenges into scalable technical solutions.
Requirements
- Individuals who are completing or have recently completed a PhD degree in Computer Science or a related discipline.
- Solid programming skills in one or more general-purpose programming languages, including but not limited to Go, C/C++, Java, or Python.
- Familiarity with basic data structures, algorithms, and Linux development environment.
- Strong coding, debugging, and system design fundamentals.
- Strong analytical thinking skills and essential knowledge of statistics, probability, and machine learning fundamentals.
- Good theoretical grounding in machine learning and deep learning concepts and techniques.
- Familiarity with at least one mainstream machine learning framework, such as TensorFlow, PyTorch, or MXNet.
- Comfort with ambiguity and the judgment to make clear engineering trade-offs.
- Strong communication and collaboration skills, with the ability to work effectively in a cross-functional environment.
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