Generative AI Engineer

1 day ago

Greater Bengaluru Area, IN Adamas Tech Consulting Full time

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, DALL·E), 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

  • Bachelor’s or Master’s degree in Computer Science, AI, ML, Data Science, or related field.

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