Product Manager I - AI Product Manager

Role Description

Job Summary

We are seeking an AI Product Manager with deep expertise in the Manufacturing Domain. You will lead the end-to-end development of AI-powered solutions, from identifying high-value use cases on the production floor to overseeing the deployment of scalable models. Your goal is to use data as a force multiplier to improve operational efficiency, reduce downtime, and enhance product quality.

Key Responsibilities

Strategy & Vision: Define a compelling AI product roadmap that aligns with manufacturing business goals and market trends. Bridges the gap between factory needs and technical capabilities; defines KPIs like OEE (Overall Equipment Effectiveness).
Use Case Discovery: Identify opportunities for AI to solve specific manufacturing needs, such as real-time anomaly detection, demand forecasting, and automated maintenance scheduling.
Cross-Functional Leadership: Partner closely with data scientists, ML engineers, and factory stakeholders to translate business problems into technical data requirements.
Data Strategy: Manage data pipelines and ensure the availability of clean, high-quality data for training and validating models.
Lifecycle Management: Oversee the entire AI product lifecycle, including prototyping, testing, deployment, and monitoring for model drift.
Performance Tracking: Define and monitor both business KPIs (e.g., ROI, cost savings) and AI-specific metrics (e.g., accuracy, precision, latency).

Required Skills & Qualifications

Domain Expertise: Strong understanding of manufacturing processes, production planning, and supply chain dynamics. A plant manager or process SME who understands machine behavior and "noise" in factory data
AI/ML Literacy: Solid grasp of ML concepts (supervised/unsupervised learning), neural networks, and computer vision.
Technical Proficiency: Ability to collaborate on data pipelines, MLOps, and technical feasibility assessments.
Strategic Thinking: Experience in prioritizing features and managing roadmaps under conditions of uncertainty.
Communication: Skill in explaining complex AI concepts to non-technical factory managers and leadership.
Ethical Oversight: Knowledge of AI ethics, including data privacy, bias, and transparency standards.

Preferred Qualifications

Proven Experience: 5+ years in product management with a focus on AI/ML or manufacturing tech.
Education: Degree in Data Science, Computer Science, or Engineering; an MBA is a plus.
Tools: Familiarity with AI frameworks (e.g., TensorFlow, PyTorch) and manufacturing software (e.g., ERP, MES).

Skills

product management,mlops architecture,ai product management,data science,

Product Manager I - AI Product Manager

Key Skills

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