CrowdStrike, Inc.

CrowdStrike, Inc.

AI Research Scientist, Agentic Systems (Remote)

USA - Remote

Sponsorship not specified$120k-$180kDetected 5 days ago
PythonReactDistributed SystemsAlgorithmsMachine LearningPyTorchData ScienceNLPLLMsAgentic AIStatisticsA/B TestingCybersecuritySOC OperationsResearchExperimental DesignWriting

Stay score

odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

Employer immigration record

from this employer's Department of Labor filings

Green-card follow-through: 100%

Of 19 labor certifications old enough to have been used, 0 expired without the employer filing the next step. Median time from filing to decision: 496 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

28 transfer filings in the last year, covering 28 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • CrowdStrike's cybersecurity data is one-of-a-kind: we process nearly a trillion behavioral events per day.
  • 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

Responsibilities

  • 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
  • Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections

Requirements

  • Experience training generative models, with a strong command of LLM training fundamentals (architecture, optimization, tokenization, data, and scaling behavior)
  • Experience with agent safety and guardrails: sandboxing, abuse/jailbreak resistance, and reliability for autonomous systems

Nice to have

  • 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)
  • Ability to work independently on ambiguous and complex objectives, and to communicate clearly within a large project team
  • 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)
  • 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
  • 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

Skills

  • Ready to join a mission that matters?

Compensation

  • Market leader in compensation and equity awards

Benefits

  • Market leader in compensation and equity awards
  • Competitive vacation and holidays for recharge
  • Paid parental and adoption leaves
  • 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
  • Excellent foundations in machine learning, probability, and statistics, with sound instincts for uncertainty, statistical skew/variance, and experimental design
  • Reinforcement learning / post-training as a core skill: RLHF/RLAIF, policy optimization (PPO/GRPO/DPO), reward modeling, and building RL environments for agents

Company info

  • 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 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.
Apply directly at CrowdStrike, Inc. →Create a free account for alerts like thisView CrowdStrike, Inc. immigration profile

This listing is sourced directly from CrowdStrike, Inc.'s careers page and normalized into a canonical job model.