CrowdStrike

Senior Engineer – Machine Learning Platform

CrowdStrike

full-time

Posted on:

Origin:  • 🇮🇳 India

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Job Level

Senior

Tech Stack

AirflowApacheCloudCyber SecurityDistributed SystemsGoGoogle Cloud PlatformGRPCJavaJenkinsKubernetesPythonRayScalaSparkTerraform

About the role

  • Charter: ML Platform team builds tools for exploration, model development, ML engineering and insights activation on the Data LakeHouse
  • Work with hyper-scale Data Lakehouse (>200 PB), batch and near real-time ingestion used for threat analytics
  • Build ML Experimentation Platform from ground up and enable self-service for thousands of users
  • Design, implement, and maintain scalable ML pipelines for data preparation, cataloging, feature engineering, training and model serving
  • Collaborate with Data Platform Software Engineers, Data Scientists, and Threat Analysts
  • Modularize ML code into standard components and establish repeatable patterns for development, deployment, and monitoring
  • Leverage workflow orchestration, Kubernetes, blob storage, and queues in a cloud-first environment
  • Review data scientist code and champion software development best practices
  • Contribute to production-focused culture bridging model development and operational success
  • Future plans include generative AI investments for modeling attack paths
  • Candidates must be comfortable visiting the office once a week

Requirements

  • B.S. in Computer Science, Data Science, Statistics, Applied Mathematics, or related field with 10+ years experience; or M.S. with 8+ years; or Ph.D. with 6+ years
  • 3+ years experience developing and deploying machine learning solutions to production
  • Familiarity with typical machine learning algorithms and supervised/unsupervised approaches
  • 3+ years experience with ML platform tools (Jupyter, NVidia Workbench, MLFlow, Ray, Vertex AI, etc.)
  • Experience building data platform products using Apache Spark, Flink or comparable tools in GCP
  • Experience with Iceberg (highly desirable)
  • Proficiency in distributed computing and orchestration technologies (Kubernetes, Airflow)
  • Production experience with infrastructure-as-code tools such as Terraform, FluxCD
  • Expert-level experience with Python; Java/Scala exposure recommended
  • Ability to write Python interfaces for data scientists to use internal tools
  • Expert-level experience with CI/CD frameworks such as GitHub Actions
  • Expert-level experience with containerization frameworks
  • Strong analytical and problem solving skills
  • Exceptional interpersonal and communication skills
  • Distributed systems knowledge
  • Data platform experience
  • Machine learning concepts
  • Desirable: Go, Iceberg, Pinot or other time-series/OLAP database, Jenkins, Parquet, Protocol Buffers/gRPC