Requirements
- 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
- 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
- (Desirable) Experience in the Advertising domain
- (Desirable) Contributions to open-source ML projects
What the job involves
- 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
- 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