Research Engineer – Generative AI and Computer Vision

Role Overview

The Research Engineer – Generative AI and Computer Vision focuses on advancing state-of-the-art Generative AI and deep learning methods for real-world computer vision applications. The role combines applied research, experimentation, and engineering to develop robust AI solutions for image understanding, synthetic data generation, visual inspection, and continuous model monitoring. The work will address practical challenges such as limited or imbalanced training data, rare events, changing image conditions, data drift, and model-performance degradation in operation.

Responsibilities

• Research, design, and implement Generative AI approaches for creating realistic and diverse synthetic image datasets using Diffusion Models and GANs.
• Develop and evaluate deep learning models for industrial image inspection tasks including classification, defect detection, and segmentation using CNNs and Transformers.
• Investigate data-efficient learning methods such as transfer learning, self-supervised learning, and few-shot learning.
• Develop methods for continuously monitoring deployed inspection models for data drift and performance degradation.
• Formulate research hypotheses, design controlled experiments, and establish evaluation benchmarks.
• Build proof-of-concept solutions and research prototypes using Python and modern deep learning frameworks.
• Collaborate with software, cloud, and MLOps teams to integrate validated methods into scalable AI platforms.
• Translate research outcomes into production-ready AI components and contribute to intellectual property.

Requirements

• Ph.D., M.S., or M. Tech from top institutes (IITs, IIITs, IISc, etc.) in Computer Science, AI, Machine Learning, or a closely related field.
• At least 3 years of relevant professional or applied research experience in computer vision, deep learning, or Generative AI.

Skills

• Python
• PyTorch
• Generative AI
• Computer Vision
• Deep Learning