Generative AI Engineer

Key Responsibilities :

• Design, develop, and deploy advanced

  image and video generation systems

  using deep learning models.
• Lead research and prototyping of

  diffusion

  ,

  GAN

  , and

  transformer-based

  architectures for generative tasks.
• Optimize models for quality, speed, and scalability using

  accelerated compute (CUDA, TensorRT, etc.)

  .
• Work with cross-functional teams (Product, Design, Frontend) to integrate AI pipelines into production apps or platforms.
• Contribute to system architecture and ensure

  reproducibility, versioning, and evaluation

  of models.
• Evaluate new advancements in generative AI and drive

  R&D to production

  transition.

Required Qualifications :

• 2+ years of hands-on experience in AI/ML with a strong focus on generative models.
• Proven experience working with video generation models (e.g., Sora, Gen-2 by Runway, Synthesia, or custom pipelines).
• Strong background in image generation using Diffusion Models (Stable Diffusion, DALL·E, Imagen) or GANs (StyleGAN2/3).
• Proficient in Python and deep learning libraries: PyTorch, TensorFlow, or JAX.
• Experience with training large-scale models using multi-GPU setups (e.g., DDP, DeepSpeed, or Hugging Face Accelerate).
• Solid knowledge of computer vision, image processing, and neural rendering techniques.
• Hands-on with model fine-tuning, LoRA/PEFT, ControlNet, DreamBooth, etc.

Preferred Tools & Frameworks :

• Stable Diffusion, DALL·E, MidJourney, Sora, Gen-2, VQ-GAN, Pix2Pix, CycleGAN, AnimateDiff
• ControlNet, T2I-Adapter, VideoCrafter, Pika Labs, ZeroScope, ModelScope
• FastAPI, Flask, or gRPC for serving models
• Streamlit, Gradio, or React (frontend) for rapid prototyping
• AWS / GCP / Azure, especially with GPU instances
• TorchServe, NVIDIA Triton, or Vertex AI for scalable model serving