Director, Model Post-Training and Agentic Research

DirectorDirectorFull TimeRemoteLeadTeam 5,001-10,000Since 2011H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

1 day ago

Salary

$195K - $290K / year

Seniority

Lead

Postgraduate Degree8 yrs expEnglish

Job Description

Director, Model Post-Training and Agentic Research

CrowdStrike

• 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.

Job 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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