Pinterest is one of the fastest growing online advertising platforms. Continued success depends on the machine-learning systems, which crunch thousands of signals in a few hundred milliseconds, to identify the most relevant ads to show to pinners. Youll join a small team, which designs high-performance and efficient ML systems, in order to power the most critical, revenue-generating algorithms and models at Pinterest.
What youll do
- Architect infrastructure solutions that directly power new algorithms and deep learning models for feature engineering and model training.
- Apply infrastructure optimizations to improve efficiency and performance for ads machine learning serving and training systems.
- Use modern stream processing frameworks to power pacing and delivery optimization algorithms, that directly improve revenue and ads quality.
- Work closely with Ads quality teams, design ML ecosystem solutions and tools to improve Ads machine learning innovation velocity.
- Partner with data and infrastructure teams inside Pinterest, to up-level the development, deployment, and monitoring tools for all Ads Serving engineers.
What were looking for:
- 5+ years of relevant industry experience
- Extensive experience with large-scale distributed systems, such as batch/streaming big-data processing, and machine-learning serving and training infra at scale
- Strong communicator and team player. Being able to find solutions for open-ended problems.
- Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
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