Director, Model Post-Training and Agentic Research

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🔥 7 minutes ago

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CrowdStrike

5001 - 10000 employees

Founded 2011

🔒 Cybersecurity

☁️ SaaS

🤖 Artificial Intelligence

Cybersecurity • SaaS • Artificial Intelligence

CrowdStrike is a cybersecurity company that provides cloud-based security services to stop breaches. It is recognized as a leader in endpoint protection, identity and cloud security, and managed detection and response. CrowdStrike's platform, Falcon, integrates artificial intelligence to offer real-time visibility, detection, and protection against sophisticated cyber threats. The company is lauded for its effectiveness in securing networks and data, making it a trusted partner for businesses worldwide.

📋 Description

• Own and personally drive the full post-training pipeline for security-domain AI — SFT, RLHF/RLAIF, agent-RL, and reward modeling. • Set research priorities and architectural direction, and lead experimental work on the hardest problems yourself rather than delegating them away. • Design reward modeling methodology grounded in verified security outcomes rather than proxy signals, drawing on both human expert feedback and automated adversarial evaluation. • Define data curation standards across sourcing, filtering, quality scoring, and domain weighting that drive measurable capability improvement. • Build and maintain agent-RL training environments that simulate realistic cyber workflows contributing directly to environment design and reward shaping. • Lead the design and build of the agent harnesses that run on top of those trained models: scaffolding architecture, tool-calling interfaces, planning and reasoning loops, and memory and context management. • Develop and own evaluation methodology for the full agentic stack, not model capability in isolation, but harness behavior, tool-use reliability, planning coherence, and end-to-end task completion across realistic security workflows. • Partner closely with other teams to ensure post-training and agentic work integrates cleanly with the broader model development loop. • Contribute original research through publications, external presentations, and open-source artifacts where appropriate, building CrowdStrike's credibility as a research-first organization in this space.

🎯 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-training stack, including SFT data pipelines, RLHF/RLAIF, PPO or similar RL algorithms applied to language models, and reward model design and training. • Demonstrated experience designing or building agentic system harnesses for LLM-based agents, including tool-use frameworks, planning scaffolds, multi-step execution environments, and context or memory management. • Strong evaluation instincts: experience designing evaluation protocols that are resistant to overfitting, capable of measuring genuine capability improvement, and interpretable to both technical and non-technical stakeholders. • Track record of running high-velocity research programs with disciplined tracking and fast iteration. • Proven ability to lead and grow research teams while remaining a credible, active technical contributor.

🏖️ Benefits

• Market leader in compensation and equity awards • Comprehensive physical and mental wellness programs • Competitive vacation and holidays for recharge • Paid parental and adoption leaves • Professional development opportunities for all employees regardless of level or role • Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections • Vibrant office culture with world class amenities • Great Place to Work Certified™ across the globe

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