Data Scientist (Remote)
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About the role
The Data Science team is expanding and is looking for a Data Scientist to help build the next generation of agentic systems for cybersecurity. CrowdStrike's cybersecurity data is one-of-a-kind: we process nearly a trillion behavioral events per day. You'll work where Machine Learning, Big Data, and Cybersecurity converge - training models, building AI agents, and rigorously measuring whether they work - on data and problems you won't find anywhere else.
Responsibilities
- Work at the intersection of Artificial Intelligence and Threat Research
- Work closely with subject-matter experts in cybersecurity to understand analyst workflows and their security operations procedures
- Post-train LLMs and agents - supervised fine-tuning and reinforcement learning (RLHF/RLAIF, PPO/GRPO/DPO, reward modeling) - to automate analyst procedures and improve reliability on real security tasks
- Devise AI agents and combine them into increasingly complex workflows: planning and reasoning loops, tool and function calling, and retrieval and memory
- Research new approaches to agentic planning, and prototype state-of-the-art methods from the literature
- Establish objective criteria for benchmarking agentic systems - evals, LLM-as-judge pipelines, and trajectory-level metrics, with real statistical rigor
- Optimize prompts and inference to get the most out of every model
- Collaborate and coordinate across Engineering, Data Science, and Managed Services teams, and partner with engineers to take prototypes toward production
- Keep track of developments in the field of Artificial Intelligence and help identify, define, and prioritize areas for research
Requirements
- Excellent foundations in machine learning, probability, and statistics, with sound instincts for uncertainty, statistical skew/variance, and experimental design
- PhD-level depth of understanding in modern machine learning research -a doctorate itself is not required, but we expect equivalent mastery, including the ability to read, critique, implement, and improve upon current papers
- Experience training generative models, with a strong command of LLM training fundamentals (architecture, optimization, tokenization, data, and scaling behavior)
- Reinforcement learning / post-training as a core skill: RLHF/RLAIF, policy optimization (PPO/GRPO/DPO), reward modeling, and building RL environments for agents
- Experience building agentic systems: agent architectures (ReAct, planning, reflection), tool and function calling, and retrieval/memory/context management
- Experience with systematic prompt optimization, and with designing and building evals for LLM systems
- Fluency with GPUs, PyTorch, and the common LLM training and serving stack (e.g., Hugging Face Transformers/TRL/PEFT, DeepSpeed/FSDP, vLLM/TGI/SGLang)
- Strong, reproducible research engineering: clean Python and disciplined experiment tracking that your collaborators can build on
- Ability to work independently on ambiguous and complex objectives, and to communicate clearly within a large project team
- Bonus Points:
- Experience generating training data and environments - synthetic data, agent trajectories/rollouts, and task simulators
- Familiarity with inference-time scaling / test-time compute (search, self-consistency, verifier-guided decoding, long chain-of-thought)
- Experience with agent safety and guardrails: sandboxing, abuse/jailbreak resistance, and reliability for autonomous systems
- A knack for interpretability and failure analysis - diagnosing why a model or agent fails, not just that it does
- Notable open-source contributions and excellent technical writing
- Passionate about cybersecurity, with a firm understanding of the problem space - or passionate about applying your machine-learning skillset to a new domain such as cybersecurity (a security background is a plus, not a requirement)
- An independent self-starter who likes to take ownership and seeks out new challenges, and is thirsty for knowledge - never hesitant to step outside your comfort zone to learn new technologies, algorithms, and concepts
- #LI-Remote
- #LI-RC1
- Benefits of Working at Cr
Benefits
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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