The candidate will create models & systems & analyze data for the privacy-preserving ad delivery system that is built into Brave.
The candidate will work continuously with both researchers & engineers.
- close familiarity with ad tech
- familiarity with Thompson sampling, contextual bandits, & related techniques
- familiarity with privacy-preserving ML techniques
- familiarity with security & fraud prevention (optional)
- ability to read & understand scientific papers & to reduce research findings into practice
- experience with software development via distributed development teams
- comfortable working in an open source setting
- excellent written & verbal communication skills in English
- proven record of getting things done
- good knowledge of python, or other language for model training, working knowledge of C++/Rust for browser components
- MS or PhD in Computer Science; we may consider a related quantitative discipline in exceptional cases
We expect the successful candidate to have experience with most widely-used languages, platforms, & libraries & to learn things on the spot whenever necessary. Experience with both building & deployment models using cloud backends such as AWS or Azure is required, however.