Engineer II - Automation & Development (Remote)

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. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward.

About the role

CrowdStrike is looking for an Applied Scientist II to join our growing team. As an applied scientist, you will contribute to the research, development, and deployment of machine learning models that power cost attribution and cloud efficiency at CrowdStrike. The candidate will play a role in analyzing large-scale cloud usage and financial datasets, building and evaluating models, and working closely with engineering teams to bring models into production. If you are interested in working on a high-performing team applying machine learning to real-world cost optimization and financial accountability problems, this is the job for you.

• Be an energetic self-starter with the ability to take ownership and be accountable for deliverables, both individually and as part of a team
• Collaboratively brainstorm, define, and build machine learning solutions to accurately attribute cloud costs and resource consumption to the teams and products driving them
• Work with internal business partners and senior scientists to analyze requirements and translate them into well-scoped modeling problems related to cost allocation, forecasting, and anomaly detection
• Design, run, and evaluate experiments to validate model accuracy in attributing costs to owning teams, products, and business units
• Contribute to raising the technical IQ of the team by staying curious and sharing new techniques and research with others
• Partner with engineering teams to help productionize models and monitor their performance and accuracy over time
• Report regularly on the status of assigned projects

Responsibilities

• U.S. citizenship or Green Card/permanent resident status
• Develop, train, and evaluate machine learning models (e.g., classification, clustering, anomaly detection, or regression) applied to structured business or financial data
• Work with large-scale datasets and distributed data processing tools (e.g., Spark, Pandas at scale)
• Apply solid understanding of statistics, probability, and experimental design
• Perform feature engineering and model evaluation techniques (e.g., precision/recall, RMSE, cross-validation)
• Query data from relational databases using SQL
• Collaborate with senior scientists and engineers, demonstrating a passion for learning new techniques, tools, and research
• Write clean, well-tested, and reproducible code with strong attention to detail
• Ensure data accuracy and integrity when working with financial and cost datasets
• Work effectively and professionally with cross-functional groups as part of a worldwide team

Requirements

• Proficiency in Python and common ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Experience working with cloud cost/billing data (e.g., AWS Cost Explorer, GCP Billing, Azure Cost Management) or FinOps practices
• Understanding of MLOps concepts and tools (e.g., model versioning, monitoring, CI/CD for ML)
• Exposure to big data / streaming platforms (e.g., Kafka, Spark Streaming)
• Familiarity with cloud platforms (AWS, GCP, Azure) for training and deploying models
• Experience with resource tagging, cost allocation frameworks, or chargeback/showback systems
• Exposure to time-series forecasting techniques for cost or usage prediction
• Experience publishing research or contributing to open-source ML projects
• Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes

Benefits

• Market leader in compensation and equity awards
• Comprehensive physical and mental wellness programs
• Competitive vacation and holidays for recharge
• Paid parental and adoption leaves
• Professional development opportunities for all employees regardless of level or role
• Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections
• Vibrant office culture with world class amenities
• Great Place to Work Certified™ across the globe

Pay

The base salary range for this position for all U.S. candidates is $100,000 - $145,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.