About the Internship CrowdStrike is looking to fill a Summer 2025 Internship with our Applied Machine Learning team. The team is focused on improving the detection capability and efficiency of the Falcon platform through employing Machine Learning algorithms to detect different types of attacks. You will have the opportunity to apply your coding and machine learning skills to the bleeding edge of security technology.

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. We are a diverse and multidisciplinary team, and you’ll have the chance to broaden your horizons by working jointly with a team of Big Data, Machine Learning and Security domain experts on challenging and impactful problems. You will gain valuable experience in a fast-paced high-growth environment.

We offer:

• Ongoing learning and development opportunities. The opportunity to leverage the AWS cloud stack for extracting features and deploying state-of-the art ML malware classifiers that learn from extremely large amounts of sample files.
• Develop Machine Learning expertise and coding skills - we use Python, Sklearn, XGBoost and related Deep Learning frameworks (Tensorflow, Keras, Pytorch); we use Git versioning control, Continuous Integration and Docker to deploy our models in the cloud.
• Assigned Mentor
• Virtual/Remote Internship with flexible working hours
• Global Intern Events, Socials, Swag & International Workshops

You will:

• Work directly with Sr. Applied Machine Learning Engineers, helping to create predictive machine learning models and tooling to improve the existing models so that we will continue to detect and stop today's most sophisticated threats
• Implement and experiment with new algorithms and methodologies to help improve our machine learning models
• Automate and visualize analyses, results, and processes in our machine learning pipeline

What You'll Need:

• 3rd or final year Computer Science student (also will consider Master/PhD students)
• Good understanding of basic ML algorithms and techniques and their tradeoffs
• Experience in writing Python code to pre-process and analyze data to generate actionable insights
• Hands on in your approach to understanding data and learning about new fields
• Passionate to develop your knowledge and learn new technologies, algorithms and concepts
• Experience with working in a Linux environment
• Good verbal and written communication skills in English

Bonus Points:

• Hands on experience with traditional Machine Learning libraries (xgboost, sklearn, etc) and/or deeplearning frameworks (Tensorflow, Keras, PyTorch)
• Good understanding of basic Machine Learning Techniques (SVM, Logistic Regression etc)
• Security Enthusiast