Data Scientist

Job Description:

We are seeking a skilled Data Scientist with expertise in computer vision to join our team. The ideal candidate will have hands-on experience in training, deploying, and maintaining computer vision models on cloud platforms and virtual machines to optimize manufacturing operations. You will work closely with cross-functional teams to develop AI-driven solutions for quality control, compliance, safety, defect detection, process automation, and predictive maintenance in manufacturing environments

Key Responsibilities:

• Model Development & Training: Develop, train, and fine-tune computer vision models for applications such as defect detection, object recognition, and anomaly detection in manufacturing.
• Deployment & Optimization: Deploy and optimize AI models on cloud platforms (AWS, Azure, GCP) and on-premises virtual machines, ensuring scalability and efficiency.
• Model Maintenance: Monitor model performance in real-time, troubleshoot issues, and implement updates to improve accuracy and reliability.
• Data Processing & Management: Work with large-scale image and video datasets, applying preprocessing, augmentation, and annotation techniques.
• Automation & Pipelines: Develop and maintain MLOps pipelines for continuous integration and deployment (CI/CD) of AI models.
• Collaboration & Reporting: Work with manufacturing engineers, IT teams, and stakeholders to understand business needs, provide insights, and present findings through reports and dashboards.
• Hands-on experience with YOLO (e.g., YOLOv5, YOLOv8) and NVIDIA DeepStream for real-time vision applications.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
• 3+ years of experience in computer vision, deep learning, and machine learning for industrial or manufacturing applications.
• Proficiency in Python, TensorFlow, PyTorch, OpenCV, and other deep learning frameworks.
• Experience deploying models on cloud services (AWS, Azure) and virtual machines.
• Strong knowledge of Docker, Kubernetes, and CI/CD pipelines for ML deployment.
• Hands-on experience with MLOps, model monitoring, and performance optimization.
• Familiarity with edge computing and IoT platforms for real-time AI applications.
• Strong problem-solving skills and ability to work in a fast-paced industrial setting.

Preferred Qualifications:

• Experience with PLC integration, SCADA systems, or industrial automation.