Help design, build, and facilitate adoption of a modern Data+ML platform
Modularize complex ML code into standardized and repeatable components
Establish and facilitate adoption of repeatable patterns for model development, deployment, and monitoring
Build a platform that scales to thousands of users and offers self-service capability to build ML experimentation pipelines
Leverage workflow orchestration tools to deploy efficient and scalable execution of complex data and ML pipelines
Review code changes from data scientists and champion software development best practices
Leverage cloud services like Kubernetes, blob storage, and queues in our cloud first environment
Requirements
B.S. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field and 10+ years related experience; or M.S. with 8+ years of experience; or Ph.D with 6+ years of experience.
3+ years experience developing and deploying machine learning solutions to production.
Familiarity with typical machine learning algorithms from an engineering perspective (how they are built and used, not necessarily the theory); familiarity with supervised / unsupervised approaches: how, why, and when and labeled data is created and used.
3+ years experience with ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLFlow, Ray, Vertex AI etc.
Experience building data platform product(s) or features with (one of) Apache Spark, Flink or comparable tools in GCP.
Experience with Iceberg is highly desirable.
Proficiency in distributed computing and orchestration technologies (Kubernetes, Airflow, etc.)
Production experience with infrastructure-as-code tools such as Terraform, FluxCD
Expert level experience with Python; Java/Scala exposure is recommended.
Ability to write Python interfaces to provide standardized and simplified interfaces for data scientists to utilize internal Crowdstrike tools.
Expert level experience with CI/CD frameworks such as GitHub Actions.
Expert level experience with containerization frameworks.
Strong analytical and problem solving skills, capable of working in a dynamic environment.
Exceptional interpersonal and communication skills. Work with stakeholders across multiple teams and synthesize their needs into software interfaces and processes.
Tech Stack
Airflow
Apache
Cloud
Google Cloud Platform
Java
Kubernetes
Python
Ray
Scala
Spark
Terraform
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