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.