AI Vision System Engineer

Factree Ai; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Factree Ai in Bengaluru, India is seeking an AI Vision System Engineer to design production-grade computer vision pipelines that connect cameras, AI models and industrial machines.

You will work with mechanical, electrical and automation teams to deploy AI-driven inspection systems on production lines, focusing on reliability, speed and real-world robustness.

The role requires hands-on CV experience, Python skills and OpenCV expertise, with a path to scalable edge deployments.

Qualifications

• At least 1 year of hands-on experience in computer vision engineering.
• Strong programming ability in Python.
• Experience building image processing pipelines using OpenCV.
• Ability to dive deep to understand and solve complex engineering problems independently.

Responsibilities

• Develop image processing pipelines using Python and OpenCV.
• Design robust preprocessing, feature extraction and inference workflows.
• Optimize algorithms for speed, reliability and scalability.
• Build real time image analysis systems that operate reliably on production lines.
• Integrate trained ML models into production inference pipelines.
• Design decision logic that converts model outputs into actionable results.
• Ensure stable performance across different lighting conditions, parts and environments.
• Develop backend services and APIs using Flask or FastAPI.
• Design database structures to store inspection results, logs and production data.
• Build modular software architectures that can scale across multiple machines.
• Work with GitHub, Docker, CI/CD pipelines, JIRA and Confluence.
• Integrate AI systems with cameras, sensors and industrial equipment.
• Deploy vision systems on edge computing platforms.
• Troubleshoot image acquisition, synchronisation and system performance.
• Collaborate with mechanical and automation engineers during machine commissioning.
• Validate system performance in real production environments.
• Investigate false detections, edge cases and system failures.
• Continuously improve model performance, inference speed and system reliability.

Skills

Hands-on computer vision engineering

Python programming

Problem solving independently

Tools

OpenCV

Python

Flask

FastAPI

Docker

GitHub

CI/CD

JIRA

Confluence

Job description

Job Summary

As an AI Vision System Engineer, you will build production grade computer vision models that will be deployed in real factories. Your work will involve designing end to end vision pipelines that connect cameras, AI models and industrial machines. The role focuses on building reliable systems that perform consistently in real world environments. You will work closely with mechanical, electrical and automation teams to deploy AI driven inspection systems on production machines.

Requirements

• At least 1 year of hands-on experience in computer vision engineering
• Strong programming ability in Python
• Experience building image processing pipelines using OpenCV
• Ability to dive deep to understand and solve complex engineering problems independently

Responsibilities Computer Vision System Development

• Develop image processing pipelines using Python and OpenCV.
• Design robust preprocessing, feature extraction and inference workflows.
• Optimize algorithms for speed, reliability and scalability.
• Build real time image analysis systems that operate reliably on production lines.

AI Model Integration and Deployment

• Integrate trained machine learning models into production inference pipelines.
• Design decision logic that converts model outputs into actionable results.
• Ensure stable performance across different lighting conditions, parts and environments.

Software Architecture

• Develop backend services and APIs using frameworks such as Flask or FastAPI.
• Design database structures to store inspection results, logs and production data.
• Build modular software architectures that can scale across multiple machines.
• Work with engineering tools such as GitHub, Docker, CI CD pipelines, JIRA and Confluence.

Industrial Vision System Integration

• Integrate AI systems with cameras, sensors and industrial equipment.
• Deploy vision systems on edge computing platforms.
• Troubleshoot issues related to image acquisition, synchronisation and system performance.
• Collaborate with mechanical and automation engineers during machine commissioning.

Testing Continuous Improvement

• Validate system performance in real production environments.
• Investigate false detections, edge cases and system failures.
• Continuously improve model performance, inference speed and system reliability.

Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.