About the job
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on.
Responsibilities
- Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia
- Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability.
- Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines.
- Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines.
Qualifications
Minimum
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- 3+ years of building models for business application experience
- Ph.D. in computer science, engineering, mathematics or equivalent, or experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch
- Experience in generative models (diffusion, flow, transformers)
- Hands-on experience with image/video synthesis and editing techniques
Preferred
- Publications in top-tier AI/ML/Graphics Conferences (CVPR, ICCV/ECCV, SIGGRAPH, NeurIPS, ICLR)
- Experience with controllable generation methods, including emerging approaches (familiarity with LoRA/ControlNet, parameter-efficient tuning, or test-time training a plus)
- Expertise in one or more of: harmonization, relighting, style transfer, lip-sync, segmentation, matting, depth estimation, 3D camera/scene modeling.