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.

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.

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

Engineering Manager – Data & ML Platform

Key skills