Senior Applied Scientist

We are looking for a Senior Applied Scientist with deep expertise in Generative AI, Diffusion Models, and Computer Vision to join Adobe's Applied AI team. In this role, you will architect and productionize state-of-the-art generative AI solutions, drive applied research into scalable products, and mentor a high-performing engineering team.
Responsibilities:
Design, train, and fine-tune large-scale diffusion models (DDPM, DDIM, LDM, DiT) for image, video, and multimodal generation.
Develop production-grade computer vision solutions using ViT, CLIP, DINOv2 SAM, and related vision foundation models.
Build controllable generative AI systems leveraging ControlNet, IP-Adapter, LoRA, adapters, inpainting, and image editing techniques.
Own the end-to-end ML lifecycle, including data preparation, model training, evaluation, optimisation, deployment, and monitoring.
Optimise large-scale models using PyTorch, ONNX, Flash Attention, xFormers, and distributed training frameworks (DDP, FSDP, DeepSpeed).
Lead technical design, mentor engineers, and collaborate with research, product, and infrastructure teams to deliver production-ready AI solutions.
Requirements:
10 + years of industry or research experience in Machine Learning/Applied AI.
MS/PhD in Computer Science, Machine Learning, AI, Statistics, or a related field.
Expert-level Python and PyTorch.
Strong expertise in Diffusion Models, Computer Vision, Vision Foundation Models, and Generative AI.
Experience training and fine-tuning large-scale vision and generative models.
Hands-on experience with distributed GPU training and MLOps tools.
Proven track record of deploying ML models to production at scale.
Preferred Qualifications:
Experience with Flow-based Generative Models, Video Generation, 3D Generative AI, and Multimodal AI (LLMs + Vision).
Exposure to RLHF/DPO for model alignment.
Active contributions to open-source AI projects (e. g., Hugging Face Diffusers, timm, CompVis) and a strong GitHub profile.

Experience
8-12 yrs