Own an end-to-end project from idea to functioning prototype, with a clear path to production.
Develop Backend Services: Design and build services in Python that power AI-driven products and shared capabilities.
Integrate Systems: Build resilient service integrations across internal systems, handling failure modes and rate limits.
Build AI Features: Develop and evolve LLM-backed features and agentic workflows, focusing on reliability and real-world behavior.
Collaborate Cross-Functionally: Work with product managers, researchers, and senior engineers to turn loosely defined AI use cases into concrete, production-ready systems.
Shape AI Quality: Help build or extend evaluation harnesses, benchmarks, or feedback loops for AI-powered features.
Engage in Sprints: Work at a fast pace in two-week sprints and participate in weekly meetups to share progress and technical challenges.

Currently enrolled in a PhD program in Computer Science, Software Engineering, or a related quantitative field, graduating in 2027
Excellent modern Python engineering skills, with the ability to write readable, performant, and testable code.
A strong background in AI/ML and experience with independent projects using LLMs, foundation models, or retrieval-augmented generation (RAG).
Solid understanding of software engineering principles, including APIs, version control, and system architecture.
Excellent communication skills and a collaborative approach to solving complex problems.
Curiosity about applying AI to cybersecurity or hands-on experience in the domain.

1:1 mentorship
The opportunity to expand your knowledge and work on challenging projects
Training and Development opportunities
Connections to other recent grads, and employees across the company
Leadership speaker series where you can learn about other areas of the business and ask questions to the senior leadership team and industry experts
Fun events!

AI/Machine Learning Engineer Intern

Key skills