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Strong employer brand and metro location balanced by senior niche ML platform specialization.
Requires deep ML platform and data engineering expertise, limiting cross-industry transferability.
Explicit 10+ years requirement, leadership mandate, and specific ML/platform tech needs make filters strict.
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Lead the Data & ML Platform team building and scaling ML experimentation platforms and infrastructure for data scientists, engineers, and analysts.
Own design, implementation, and maintenance of scalable ML pipelines including data prep, feature engineering, model training, deployment, and monitoring impacting critical business decisions.
Drive Generative AI initiatives and foster a production-focused culture balancing model development with operational success.
Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related; or Master's with 8+ years; or Ph.D. with 6+ years experience.
10+ years experience in data engineering, ML platform development, or related fields, including 5+ years leadership experience.
Strong familiarity with ML algorithms (supervised and unsupervised), ML platform tools (e.g., MLFlow, Kubeflow, SageMaker), and data platform technologies (e.g., Apache Spark, Flink, Kubernetes).
Work Experience Required: 10+ years overall in relevant fields with 5+ years leadership experience; Notice Period: Not explicitly mentioned in the JD.
Strategic and technically skilled leader with hands-on expertise in building and scaling ML platforms in large-scale, complex environments.
Experience in founding and expanding teams focused on ML infrastructure and experimentation platforms with a strong operational mindset.
Strong ability to engage stakeholders across product, engineering, and data science teams to align platform capabilities with business goals and drive innovation.