About the Role:
CrowdStrike is looking to fill a Summer 2026 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.
What We Offer:
Ongoing learning and development opportunities. The opportunity to leverage the AWS cloud stack for extracting features and deploying 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
State-of-the art infrastructure - H100, B200 GPU clusters
What You'll Do:
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
