Generative AI Engineer

Location: Bangalore

Experience: 7+ Years

Employment Type: Full-time

Role Overview

We are seeking an experienced Generative AI & Computer Vision Engineer to design, develop, and deploy advanced AI solutions involving image/video understanding, generative models, and deep learning architectures . The role requires strong hands-on expertise in computer vision pipelines and modern generative AI frameworks , working closely with product, data, and engineering teams.

Key Responsibilities

• Design and implement computer vision models for image/video classification, detection, segmentation, and tracking.
• Develop and fine-tune Generative AI models including GANs, Diffusion Models, and Vision-Language Models (VLMs) .
• Build end-to-end ML pipelines from data ingestion to model deployment and monitoring.
• Optimize models for performance, scalability, and latency in production environments.
• Work with large-scale image and video datasets, performing data preprocessing, augmentation, and labeling strategies.
• Integrate AI models with applications using REST APIs / microservices .
• Collaborate with cross-functional teams to translate business problems into AI-driven solutions.
• Stay updated with the latest research and industry trends in Generative AI and Computer Vision .

Mandatory Skills

• 7+ years of experience in Machine Learning / Deep Learning .
• Strong hands-on experience in Computer Vision using OpenCV, TensorFlow, PyTorch .
• Experience with CNNs, ResNet, EfficientNet, YOLO, Faster R-CNN, Mask R-CNN .
• Hands-on experience with Generative AI models such as GANs, Diffusion Models (Stable Diffusion, DALLE), VAEs .
• Strong programming skills in Python .
• Experience with model training, fine-tuning, and evaluation .
• Solid understanding of linear algebra, probability, and optimization .

Nice to Have Skills

• Experience with Vision-Language Models (CLIP, BLIP) .
• Exposure to LLMs integration for multimodal AI solutions.
• Experience deploying models on cloud platforms (AWS/GCP/Azure) .
• Knowledge of MLOps tools (MLflow, Kubeflow, Airflow).
• Experience with edge AI or real-time inference systems.

Education

• Bachelors or Masters degree in Computer Science, AI, ML, Data Science , or related field.