Strong interest in the synthesis of machine learning and security engineering: you should be comfortable discussing threats that apply to machine learning (e.g. training data leakage, prompt injection, multi-tenancy workloads, membership inference, etc.)
Experience in reviewing design and implementation of multi-component software systems, especially those which are reliant on homegrown or third-party LLMs and APIs
Ability to automate tasks, collect, integrate and analyze data from multiple sources
Ability to design and write program/design specifications for self and others
Strong communicator who is comfortable working cross-functionally, with a track record of independence and delivering results
Able to work across team boundaries, reach consensus amongst disparate view points, and graciously receive feedback
Fluency in SQL
PREFERRED QUALIFICATIONS
Familiarity with low-level GPU architecture
Data Science/ML Engineering background
Expert understanding of software security architecture and design, threat modeling, code review, SDLC best practices, and mitigations for common application security issues
Contributions to the security community, such as open source tools, research papers, conference talks, etc.
