Senior Machine Learning Scientist, Advertising

Roku•San Jose, CA

1d•$148,750 - $361,000•Hybrid

About The Position

Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time. In this role you will work on applying SOTA research and conduct your own research to develop novel methodologies to solve a large variety of challenging problems in Advertising related to conversion modeling aligned with attribution methodologies/models, calibration, dynamic creative generation and optimization, forecasting and timeseries modeling, yield and margin optimization and Experimentation for A/B and multivariate testing. We’re looking for a strong technical leader with a solid grasp of core statistical techniques and deep experience in SOTA Deep Learning discriminative and generative models.

Requirements

PhD in a quantitative discipline such as CS, Statistics, Applied Math or a related field
8+ years of experience in applied research using statistical and deep learning techniques
Published paper(s) on deep learning models for Advertising or related areas
Excellent communication and collaboration skills

Nice To Haves

Experience in the Advertising domain
Contributions to open-source ML projects

Responsibilities

Applying research and conducting your own research to build SOTA Deep learning discriminative models
Building generative models to generate image and video ads geared towards optimizing performance
Stay at the forefront of advancements in related areas