Director, Model Post-Training and Agentic Research (Remote)

About the role

The security domain presents one of the richest and most consequential training signal environments in applied AI. It's adversarial by nature, grounded in real operational outcomes, and evolving faster than any static benchmark can capture. We're building the post-training and reinforcement learning capability to build the latest models and harnesses into security-specialized systems that reason, plan, and act across complex cyber workflows. The person leading this work will be in the research, not just directing it. In this role, you'll own the full post-training stack for security-domain AI (e.g., supervised fine-tuning, reward modeling, RLHF and RLAIF pipelines, and agent-RL environments) and the agentic research that sits on top of it. That means designing, building, and evaluating the harnesses that security agents actually run on (e.g., the scaffolding, tool-use interfaces, planning loops, memory and context management, and multi-step execution frameworks) that determine whether a trained model can operate reliably on complex security tasks. Post-training and agent architecture are not separable problems in this work. The reward signal you design has to reflect what the harness can measure, and the harness has to be built to surface what training needs to optimize. You'll set the technical direction on both, and you'll be in the work on both. You'll lead a team of research scientists and engineers, but the team will look to your own work as the standard. The successful candidate shapes research priorities, keeps the team moving at high velocity across multiple training cycles per year, and elevates the quality of work by staying close enough to it to know what good actually looks like.

Responsibilities

• Recruit, develop, and retain a high-density team of research scientists and ML engineers. Set a technical bar through your own contributions, not just your standards.

Requirements

• MS or PhD in computer science, machine learning, or a related quantitative discipline.
• 8+ years of experience in ML research or engineering, with meaningful depth in large language model post-training.
• Hands-on expertise across the modern post-trai

Additional Information

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn't changed - we're here to stop breaches, and we've redefined modern security with the world's most advanced AI-native platform. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We're always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.

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