What Will You Do?
You'll be part of a team of globally distributed AI engineers and researchers, focused on bringing the most recent advances in machine learning technology to help our customers efficiently discover and defeat threats. We're the team behind products such as PurpleAI (released for general availability in April 2024, see also the latest demo), awarded one of the Top10 hottest cyber products of 2023, and more!
As a ML specialist on the team, you will ideate and create features that will help our engineering teams as well as support our customers by providing better visibility into the health of the endpoints in the field.
You will collaborate across multiple engineering teams to design and build net new capabilities that will be used across industry-leading platform.
As Staff-level engineer, you should be willing and able to inspire others and lead them technically.
As we're extending our team by more new colleagues, your focus may be directed more to either Science side (take functional requirements in ML/AI from ideation to delivery) or Platform side (efficiently deliver models & science systems into production) – depending on your skills, experience & interests.
Masters Degree in any quantitative science or engineering field. Additional or directly relevant experience will be considered in lieu of a degree
7+ years of experience solving complex problems using modern AI/ML techniques
Experience in designing, training and evaluating models
Experience with collecting, building, and tailoring large datasets for training machine learning models
Comfort-level working cross-functionally across both research and product teams
Nice to Haves:
Prior experience leading the development of generative models and their applications
Experience in software engineering and with data structures
Experience with endpoint security or OS concepts
Experience with model parallelism for working with large neural network architectures
First-author publications at peer-reviewed AI conferences
Expertise in natural language processing, especially practical experience developing modern, transformer-based language models
Experience developing complex applications leveraging API-based LLMs
