AI Engineer

DE-YAN | Where Creativity Meets Intelligence

ABOUT US

DE-YAN is a global brand experience studio headquartered in New York, working with some of the world's most iconic names — Louis Vuitton, Nike, Dior, Spotify, Google, Cartier, Tiffany & Co., and many more. We're now building an AI practice to match the ambition of our work, with a dedicated engineering team in Belgrade at its core.─

THE ROLE

We're assembling a small, elite AI engineering team in Belgrade. This is a ground-floor opportunity to shape how AI gets embedded into a world-class creative operation — from the way we measure impact to the way we run productions.

You'll work on applied AI products that touch real-world environments: think computer vision in live spaces, multimodal understanding of people and context, and intelligent tooling that makes creative teams faster and sharper.

WHAT YOU'LL DO

• Build and deploy computer vision and LLM-powered pipelines in real production environments
• Work with multimodal models (vision + language) to extract meaning from complex, unstructured scenes
• Develop AI modules that are robust, reusable, and actually used — not just prototyped
• Collaborate closely with a senior technical lead and cross-functional creative/tech teams globally
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WHAT WE'RE LOOKING FOR

• 4–5 years of hands-on experience in applied ML/AI engineering
• Solid Python and deep learning fundamentals — you understand what's happening under the hood, not just the API calls
• Hands-on experience with computer vision — object detection, tracking, scene understanding
• Familiarity with LLMs and multimodal models (vision-language models, embeddings, inference pipelines)
• Comfort working with real-world, messy data — not just clean benchmarks
• End-to-end mindset: you care about things running in production, not just in notebooks
• MSc or PhD in Computer Science, Electrical Engineering, or a related field — or equivalent demonstrated depth

NICE TO HAVE

• Experience building or fine-tuning models from scratch — deep understanding of transformer architectures beyond wrapper libraries
• AWS end-to-end experience: training, deployment, and scaling (SageMaker, EC2, Lambda, S3)
• Experience with sensor data or multi-source data fusion
• Exposure to pose estimation or person re-identification
• Real-time inference and edge/cloud deployment experience
• Interest in the events, fashion, or luxury brand industry

WHY DE-YAN

• Work on genuinely novel problems at the edge of AI and live human experience
• Clients include some of the most recognized names in global culture and brand
• New York headquartered — with real transatlantic collaboration, not just a remote outpost
• Competitive Belgrade-market compensation, benchmarked seriously
• Small team, high ownership, fast iteration