Knowledge of data query and data processing tools (i.e. SQL)
Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
Experience deploying highly scalable software supporting millions or more users
Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
Responsibilities
Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
Build "machine learning ready" feature pipelines.
Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.
Run regular A/B tests, gather data, and draw conclusions on the impact of your models.
Monitor and maintain production models.
Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.
Other
Work cross functionally with product managers, AI scientists and product engineers, and communicate results to peers and leaders.
Strong oral and written communication skills.
Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
