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Generalist Product title, mid-level (3+ years), and metro Bangalore location increase applicant competition.
Specialized AI/ML platform skills transfer across industries, but geospatial/EO domain knowledge increases sensitivity.
Explicit 3+ years plus mandatory ML/DS or AI-platform experience and proven technical product ownership.
Own the AI/ML Platform layer, focusing on reusable systems and workflows to build, govern, evaluate, deploy, and operate AI capabilities at scale.
Develop and manage the AI/ML platform roadmap, defining platform requirements, metrics, and MVP scope for capabilities such as data discovery, model governance, and observability.
Lead the platform product lifecycle from experimentation through deployment, ensuring integration with other platform pillars and maintaining operational reliability, cost, and governance trade-offs.
3+ years in relevant roles such as technical product management, ML engineering, data science, MLOps, or AI/data platforms with understanding of end-to-end ML lifecycle.
Demonstrated ownership of technical product or platform capabilities including discovery, prioritization, delivery, and adoption.
Strong analytical skills for data-driven decision making and excellent communication with cross-functional stakeholders.
Work Experience Required: 3+ years; formal PM title not mandatory but product ownership is required.
Experienced in technical product roles with focus on AI/ML platforms or data-intensive systems supporting data scientists and ML engineers.
Comfortable managing complex platform metrics (e.g., adoption, reproducibility, cost) and balancing trade-offs across reliability, governance, and cost.
Familiarity with AI/ML lifecycle, MLOps practices, and integration of model governance, observability, and data quality tooling in enterprise environments.