KEY RESPONSIBILITIES

1. AI/ML & Computer Vision

- Develop, train, test, and validate AI/ML models for industrial machine vision applications.

- Work on image classification, object detection, segmentation, defect detection, and related computer vision applications.

- Prepare and optimize datasets for AI model development.

- Perform model evaluation, validation, and performance improvement.

- Analyze model results and identify areas for improvement.

- Support deployment of AI models on production machines and inspection systems.

- Work with Python, OpenCV, and relevant AI/ML frameworks.

2. AI Model & Data Systems

- Manage image datasets required for AI model development and validation.

- Perform data collection, cleaning, annotation, labelling, and quality checks.

- Maintain proper version control and documentation of datasets and AI models.

- Develop processes for data preparation and model training.

- Monitor model performance using production data and inspection results.

- Support retraining and optimization of models based on new data.

- Maintain AI model configurations, scripts, parameters, and related technical documentation.

3.

Feasibility

Study

- Understand customer requirements and inspection challenges.

- Conduct technical feasibility studies for current machine vision and AI-based inspection applications.

- Evaluate sample parts, images, defects, lighting conditions, camera requirements, and inspection parameters.

- Identify suitable AI/ML and computer vision approaches for the application.

- Prepare feasibility reports, technical observations, and recommendations.

- Conduct proof-of-concept trials and evaluate expected inspection

performance.





- Coordinate with engineering teams for camera, lens, lighting, machine, and software requirements.

4.

Application

Engineering

- Support installation, configuration, testing, and commissioning of AI-based inspection applications.

- Integrate AI models with machine vision systems and application software.

- Configure inspection parameters based on customer requirements.

- Conduct application testing using OK and NOK samples.

- Perform validation and fine-tuning of inspection applications.

- Support Site Acceptance Testing (SAT) and customer demonstrations.

- Troubleshoot application-related issues during deployment.

- Provide technical support during production trials and implementation.

5. Customer & Project Coordination

- Understand technical requirements from customers and convert them into application requirements.

- Coordinate with internal engineering, AI/ML, software, and project teams.

- Participate in customer discussions, technical reviews, and application trials.

- Provide regular updates on feasibility studies, model development, testing, and deployment.

- Support root-cause analysis for application and inspection issues.

- Prepare technical reports, test reports, validation documents, and knowledge-transfer documents.

REQUIRED SKILLS

- Strong understanding of AI/ML and Computer Vision.

- Hands-on experience with Python and OpenCV.

- Knowledge of machine learning and deep learning concepts.

- Experience with image processing and image analysis.

- Understanding of AI model training and validation.

- Knowledge of data preparation, annotation, and dataset management.

- Ability to analyze images and identify inspection/quality challengesRole & responsibilities

📌 AI/ML & Application Engg (Machine Vision,Industrial Automation) (Pune)
🏢 Seventh Contact Hiring Solutions
📍 Pune