Director, Data & ML Platform

CrowdStrike CrowdStrike · Enterprise · Bangalore, India

CrowdStrike is seeking a Director to lead their Data & ML Platform team. This role involves defining and building an ML Experimentation Platform, scaling data and ML infrastructure, and overseeing ML pipelines for the entire lifecycle (data prep, feature engineering, training, serving, monitoring). The position also focuses on leveraging Generative AI and building an AI-powered platform for ML development, with a strong emphasis on operational excellence and stakeholder engagement.

What you'd actually do

  1. Define the vision, strategy and roadmap for the organization’s data and ML platform to align with critical business goals.
  2. Build a team of Data and ML Platform engineers and work effectively with a team distributed across the US and India
  3. Oversee the design and implementation of a platform containing data pipelines, feature stores and model deployment frameworks.
  4. Institute best practices for data security, compliance and quality to ensure safe and secure use of AI/ML models.
  5. Establish SLI/SLO metrics for Observability of the Data and ML Platform along with alerting to ensure a high level of reliability and performance.

Skills

Required

  • 10+ years experience in data engineering, ML platform development, or related fields with at least 5 years in a leadership role.
  • Familiarity with typical machine learning algorithms from an engineering perspective; familiarity with supervised / unsupervised approaches: how, why and when labeled data is created and used.
  • Deep understanding of machine learning workflows, including model training, deployment and monitoring.
  • Experience with modern ML Ops platforms such as MLFLow, Kubeflow or SageMaker preferred.
  • Experience in data platform product(s) and frameworks like Apache Spark, Flink or comparable tools in GCP and orchestration technologies (e.g. Kubernetes, Airflow).
  • Experience with boot strapping new teams and growing them to make a large impact.
  • Exceptional interpersonal and communication skills.

Nice to have

  • 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.
  • Knowledge of ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLFlow, Ray, Vertex AI, Frontier AI models, etc.
  • Experience with Apache Iceberg is a plus.
  • Familiarity with data visualization tools and techniques.

What the JD emphasized

  • build our ML Experimentation Platform from the ground up
  • scaling our data and ML infrastructure
  • model serving
  • in-field model performance monitoring
  • Generative AI investments
  • AI-powered platform for ML development
  • data pipelines
  • feature stores
  • model deployment frameworks
  • Agentic/GenAI technologies
  • ML Ops practices
  • data security, compliance and quality
  • Observability of the Data and ML Platform

Other signals

  • building ML experimentation platform from the ground up
  • scaling data and ML infrastructure
  • ML pipelines for data preparation, feature engineering, model training, model serving, and monitoring
  • Generative AI investments
  • AI-powered platform for ML development