Vision Analytics PM

Role : Vision Analytics PM

Job Summary

Key Accountabilities Areas

Key Activities

Vision Use Case Delivery

• Lead use cases involving cameras (normal/IR/RF), sensors, and AI/ML models for quality, motion tracking, or safety monitoring.
• Translating operations pain points into image/video-based solutions.

Vendor and Hardware Management

• Evaluate and manage external vendors for camera hardware, AI models, and PLC integration.
• Ensure installation, calibration, and lighting standardization.
• Manage OEM relationships for critical machines and ensure best-in-class controls and sensing is in place.

Change Management

• Facilitate engagement between operators, supervisors, and EH&S.
• Translate results into SOP updates and coordinate with process and operations team to update SOPs

Feedback Loop Closure

• Partner with IT, engineering, and OT teams to ensure the setting up of business requirements and align on annotation and other feedback
• Build automated feedback to machine control (e.g., reject logic, dryer adjustment, hopper movement) based on vision alerts.

Stakeholder Communication

• Align plant teams and project sponsors on outcomes, trials, and ROI for POCs and scaling
• Document model performance and data improvement loops with Digital and analytics teams

Value orientation

• Responsible for Quality improvement and warranty reduction through deployment of computer vision systems at various sections of shopfloor.

Required skillsComputer Vision

• Exposure to object detection/classification, segmentation, defect detection.
• Understanding of OPC UA, MQTT, camera-to-PLC interfacing, reject actuation.

Tools & Systems

• Experience with Ignition, Power BI, Rockwell HMI systems
• Python, OpenCV, etc.

Soft Skills

• Able to align process engineers and plant leadership to drive changes.
• Experience managing hardware partners and deployment lifecycle.
• Strong stakeholder management; comfort working with shopfloor teams with local language proficiency (Telugu/Tamil).

Good to have:Industry 4.0 Technologies

• Understanding of Industry 4.0 principles and their applications, including smart manufacturing, and connected systems.

Digital Tooling Awareness

• Knowledge of AI and vision systems
• Experience with digital product development

Qualifications Work Experience

• 6-10 years in industrial automation, vision systems, or smart manufacturing.

Educational Background

• B.E./B. Tech in ECE, Instrumentation, CS or equivalent.

Preferred Industry Experience

• AI or CV deployment certifications preferred.