Product Manager — AI/ML
On-sitePune, Maharashtra, India
Job Summary
Define and execute the multi-quarter roadmap for RubiStudio (AutoML, model registry, MLOps pipelines) and RubiAI (LLM-powered copilot, agentic workflows). Translate enterprise AI adoption patterns into concrete product features with measurable success criteria. Partner with applied research teams and Industry-Academia Labs to evaluate emerging AI techniques for product applicability. Conduct discovery with data science, ML engineering, and business analyst personas to identify friction in the model-to-production journey. Own responsible AI governance features including model explainability, bias detection, and compliance guardrails for BFSI and healthcare regulators. Drive go-to-market for AI/ML features with marketing and pre-sales, maintaining clear feature deprecation and versioning policies to ensure zero production disruption.
Required Qualifications
- 4–7 years of product management
- at least 2 years owning AI, ML, or data science platform products in an enterprise B2B context
- Working understanding of the ML lifecycle: data preparation, feature engineering, model training/evaluation, deployment, monitoring, and retraining pipelines
- Familiarity with LLMs, RAG architectures, and agentic AI frameworks (LangChain, LlamaIndex, or similar) at a conceptual and use-case level sufficient to write meaningful PRDs
- Ability to de-risk AI product bets through structured experimentation, user research, and prototype validation rather than speculation
- Strong communication skills to bridge data science jargon and C-suite business language in the same conversation
Desired Qualifications
- Prior experience as a data scientist, ML engineer, or quantitative analyst — giving you credibility with technical stakeholders without needing constant translation
- Exposure to AI governance frameworks (EU AI Act, RBI AI guidelines, SEBI data regulations) relevant to regulated Indian industries
- Published work, patents, or conference talks in AI/ML, data science, or related fields
- Experience with low-code/no-code ML tools and AutoML platforms (H2O.ai, DataRobot, Google AutoML, or comparable)
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