Senior Video Annotation Jobs (NOW HIRING)

Job Summary:
URBN is seeking a Senior Data Scientist to develop AI-powered visual experiences, focusing on image and video generation. The role involves leading algorithm development and generative AI initiatives, closely collaborating with various teams to drive innovation across URBN's digital ecosystem.
Responsibilities:
• Design, implement, and optimize image and video generation pipelines using state-of-the-art models to produce high-quality visual content at scale.
• Build and maintain multi-model generative workflows using orchestration tools that chain together generation, inpainting, upscaling, style transfer, and conditioning steps into production-ready pipelines.
• Fine-tune and adapt image generation models using techniques such as LoRA, DreamBooth, ControlNet, IP-Adapter, and textual inversion to achieve brand-consistent, style-controlled outputs.
• Leverage multimodal and vision-language models for image understanding, visual analysis, automated tagging, and quality evaluation within generative workflows.
• Evaluate, prototype, and integrate emerging video generation models into creative and product workflows.
• Develop agentic AI pipelines that orchestrate multi-step visual content creation, from prompt generation and image synthesis to post-processing and delivery.
• Collaborate with cross-functional teams including Creative, Product Management, and Engineering to translate brand and business needs into scalable generative AI solutions.
• Lead the technical evaluation of new generative AI models, tools, and vendors as the landscape evolves, influencing decisions for URBN's visual AI technology stack.
• Guide data curation and preparation strategies for fine-tuning, including dataset construction, annotation workflows, and synthetic data generation.
• Analyze and benchmark model outputs for quality, consistency, and brand alignment, designing robust validation and feedback loops that combine quantitative metrics with qualitative human assessment.
• Partner with engineers to translate research prototypes into production-grade services and APIs, with attention to cost optimization and throughput at scale.
Qualifications:
Required:
• 5+ years of industry experience in data science, machine learning, or AI engineering, with a strong foundation in ML fundamentals.
• 1+ year of hands-on experience working with image generation models in a professional or serious applied context, not casual experimentation.
• Strong proficiency in Python, with practical experience using ML frameworks such as PyTorch and Hugging Face multimodal models.
• Hands-on experience with image model fine-tuning and conditioning techniques.
• Working knowledge of GenAI workflow orchestration tools for building multi-step generation pipelines.
• Experience with multimodal and vision-language models for image understanding, captioning, or visual analysis.
• Experience with cloud-based AI infrastructure for training, fine-tuning, and serving generative models.
• Proven ability to evaluate and rapidly adopt new generative AI models and tools as the field evolves.
• Strong visual sensibility, with an eye for image quality, composition, and brand consistency in generated outputs.
• Excellent communication and collaboration skills, with the ability to bridge technical and creative teams.
• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Engineering, or Mathematics, or equivalent practical experience.
Preferred:
• Experience with video generation models and understanding of the evolving video GenAI landscape.
• Hands-on experience with creative design tools such as Adobe Photoshop, Firefly, or Figma, especially AI-augmented creative features like generative fill and inpainting.
• Experience building agentic AI workflows to orchestrate multi-model pipelines.
• Familiarity with fashion, retail, or e-commerce applications of generative AI, such as virtual try-on, AI product photography, or on-model image generation.
• Background in computer vision fundamentals like segmentation, detection, and embeddings that complement generative work.
• Experience with prompt engineering at scale, developing systematic prompt libraries or structured prompting strategies for consistent visual output.
Company:
URBN Urban Outfitters, Inc. Founded in 1970, the company is headquartered in Philadelphia, USA, with a team of 10001+ employees. The company is currently Late Stage.