Engineering Manager – Data, ML Platform
CrowdStrike
full-time
Posted on:
Location Type: Hybrid
Location: Bangalore • India
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About the role
- Contribute to the roadmap for the organization's data and ML platform to align with critical business goals.
- Help design, build, and facilitate adoption of a modern Data+ML platform.
- Stay updated on emerging technologies and trends in data platform, ML Ops and AI/ML.
- Build and lead a team of Data and ML Platform engineers.
- Foster a culture of innovation and strong customer commitment for both internal and external stakeholders.
- Oversee the design and implementation of a platform containing data pipelines, feature stores and model deployment frameworks.
- Develop and enhance ML Ops practices to streamline model lifecycle management from development to production.
- Institute best practices for data security, compliance and quality to ensure safe and secure use of AI/ML models.
- Partner with product, engineering and data science teams to understand requirements and translate them into platform capabilities.
- Communicate progress and impact to key stakeholders.
- Establish SLI/SLO metrics for Observability of the Data and ML Platform along with alerting to ensure a high level of reliability and performance.
- Drive continuous improvement through data-driven insights and operational metrics.
Requirements
- B.S. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field and 8+ years related experience; or M.S. with 6+ years of experience; or Ph.D with 4+ years of experience
- 8+ years experience in data engineering, ML platform development, or related fields with at least 3 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.
- Knowledge of ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLflow, Ray, Vertex AI, etc.
- 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 Apache Iceberg is a plus.
- Experience building and scaling high-performing engineering teams.
- Exceptional interpersonal and communication skills.
- Work with stakeholders across multiple teams and synthesize their needs into software interfaces and processes.
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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringML platform developmentmachine learning algorithmssupervised learningunsupervised learningML Opsdata pipelinesfeature storesmodel deployment frameworksdata security
Soft Skills
leadershipinterpersonal skillscommunication skillsinnovationcustomer commitmentcollaborationsynthesis of stakeholder needscontinuous improvementdata-driven insightsoperational metrics