UST
Website:
ust.com
Job details:
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,
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