About the Role:
CrowdStrike's cybersecurity data is one-of-a-kind: we process over 300 billion behavioral events per day, and have more than 1 petabyte of malware samples in our research repository. As a data science intern you will work closely with senior data scientists, software engineers and product managers to contribute to cutting-edge AI projects and gain hands-on experience with real-world cybersecurity challenges. You'll have access to our large-scale GPU compute clusters to train and experiment with advanced AI models.
What You'll Do:
Conduct cutting-edge research applying the latest AI technologies to real-world cybersecurity challenges.
Work directly with Sr. Data Scientists on bleeding edge applications including, but not limited to, training large language models (LLMs), developing graph neural networks, implementing optimization algorithms, and exploring tokenization methods.
Leverage large-scale data to develop new algorithms and models for synthetic data generation, predictive systems, and improving threat detection.
Automate and visualize processes throughout the AI development pipeline.
What You'll Need:
You should be working towards a University degree in a field related to Computer Science, Maths, Statistics, Engineering or similar.
Analytically minded with completed coursework in linear algebra, calculus, statistics, machine learning theory or an equivalent knowledge of applied mathematics.
Experienced in writing python code to pre-process and analyze data to generate actionable insights and train AI models.
Knowledge of object oriented programming, data structures and algorithms
Passionate about staying on top of the latest advancements in large language models, machine learning, data generation, and other AI techniques.
Bonus Points:
PhD or Master's students in a field related to Computer Science, Maths, Statistics, Engineering or similar.
Interest in contributing to and publishing research in top-tier AI/ML conferences and journals
Experience working with large datasets and machine learning models.
Familiarity with Linux, cloud computing, CI/CD pipelines, Docker, Kubernetes, etc.
Knowledge of cybersecurity challenges and how AI can be applied to tackle them.
Willing to learn to contribute to the open source community (GitHub, Stack Overflow, blogging)
