As an AI/Machine Learning Engineer Intern, you will be tasked with applying software engineering skills to create reliable, AI-powered products within a fast-paced product engineering environment. You will own an end-to-end project from initial idea to a functioning prototype with a clear path to production. Throughout the internship, you will collaborate with research teams and senior engineers to transform loosely defined AI use cases into concrete, production-ready systems.

What Will You Do?

Primary responsibilities include:

• 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, specifically handling complex failure modes and rate limits.
• Build AI Features: Develop and evolve LLM-backed features and agentic workflows, focusing on reliability and real-world behavior.
• Shape AI Quality: Help build or extend evaluation harnesses, benchmarks, and feedback loops to ensure the high performance of AI-powered features.
• Engage in Sprints: Work at a high velocity in two-week sprints and participate in weekly meetups to share technical progress and solve challenges.

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• Advanced Academic Background: Currently enrolled in a program in Computer Science, Software Engineering, or a related quantitative field (graduating in 2027).
• Python Proficiency: Excellent modern Python engineering skills with the ability to write readable, performant, and testable code.
• AI Fundamentals: A strong background in AI/ML and experience with independent projects using LLMs, foundation models, or RAG.
• System Design: A solid understanding of software engineering principles, including APIs, version control, and system architecture.
• Cybersecurity Interest: A genuine curiosity about applying AI to cybersecurity or hands-on experience in the domain.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.