Sr. Data Scientist, Applied AI/ML

About the role

CrowdStrike is seeking a Sr. Data Scientist to join our team building the next generation of AI/ML technologies. You will work closely with other scientists, software engineers and product managers to provide technical leadership and strategic direction, while driving hands-on-keyboard innovation in our AI capabilities.

Responsibilities

• Work alongside teammates to develop clever, innovative, and efficient solutions to problems in AI safety and cyber detection.
• Co-develop strategies and implementations for end-to-end research and development: data sourcing, data labeling, advanced modeling, evaluation/benchmarking, and product-ready engineering collaboration.
• Interoperate with product and engineering teams to ensure that you are designing and building the right solutions: fit-for-purpose, efficient, computable, and maintainable.
• Drive innovation in LLM-related research and development in close collaboration with security experts.
• Maintain and manage trade-offs between accuracy, efficiency, and operational costs of fielded AI/ML models.
• Make strategic decisions about GenAI model architectures, training approaches, and deployment strategies.
• Lead and architect the research strategy for new GenAI agents/LLMs, setting the technical direction for the team.
• Lead and architect the research strategy for new GenAI agents/LLMs, setting the technical direction for the team.
• Drive innovation in LLM applications, including novel approaches to reasoning, summarisation, and interactivity.
• Mentor and guide Data Scientists while fostering a culture of engineering excellence.
• Lead cross-functional initiatives and collaborate with senior leadership to align technical strategy with business goals.
• Represent CrowdStrike's technical excellence through publications, speaking engagements, and thought leadership.
• Establish best practices, technical standards, and evaluation frameworks for the team.

Requirements

• Advanced degree (PhD or Masters) in Computer Science, Data Science, or a related field.
• 7+ years of applied machine learning / research experience, with demonstrated expertise in developing production-grade models.
• Deep expertise in LLM training or post-training / deployment at scale.
• Strong technical leadership experience, including mentoring teams and driving technical strategy.
• Expert-level understanding of Python, Deep Learning frameworks, and cloud technologies.
• Advanced knowledge of GPU technologies and optimisation techniques.
• Outstanding communication skills with ability to influence senior stakeholders.
• Track record of solving complex technical challenges at scale.

Bonus points

• Patents or significant intellectual property contributions in AI.
• Strong research portfolio with publications in leading AI journals and conferences.
• Experience with cybersecurity applications of machine learning.
• Track record of successful research-to-production implementations at scale.
• History of contributions to open-source ML projects.