Machine Learning Engineer

At Bynder, we don’t just store creative assets; we enable brands to deliver exceptional content experiences that drive business impact.

In an era of exploding content volume and complexity, the world’s most iconic brands, including Spotify, Campari, and Lacoste , trust Bynder as their single source of truth for creative content . Our industry-leading DAM platform serves as the strategic engine for brand governance and control.

We are leading the shift from management to AI-powered content orchestration . By integrating human-led, customizable AI Agents directly into our enterprise-grade infrastructure, we enable brands to augment their workforce and intelligently automate high-effort workflows without sacrificing brand integrity. We turn creative content into intelligent assets that accelerate personalization and drive measurable business outcomes.

Ready to grow your career by helping the world’s leading brands deliver exceptional content experiences? Join our global team of 600+ ‘Byndies’ and help 4,000+ organizations work smarter with their content. Explore this opportunity and apply now to join our team.

About The Team Bynder AI Labs is our dedicated AI innovation team. We’re a small, high-impact group of AI experts responsible for researching, prototyping, and shipping the next generation of AI-powered capabilities for Bynder’s platform. We’ve already delivered features like AI Search and AI Agents for content enrichment, governance, compliance and transformation.

We sit at the intersection of cutting-edge AI research and practical product development. Our job is to figure out what’s possible and make it real. We are looking for a Machine Learning Engineer who wants to define what comes next.

What You Will Do

• Design, build, and deploy AI-powered features for Bynder’s DAM platform, focusing on content discoverability, automation, and intelligent workflows.
• Architect and implement solutions using AWS AI services (Bedrock, SageMaker, Lambda) and large language model APIs.
• Build and optimize embedding-based systems for AI search, semantic retrieval, and content recommendation.
• Develop agentic AI workflows that automate complex tasks such as asset enrichment, tagging, transformation, and compliance checking.
• Create production-quality prototypes and proof-of-concepts that demonstrate the value of new AI capabilities to stakeholders.
• Stay current with the rapidly evolving AI landscape and bring fresh ideas and techniques to the team.
• Collaborate with the broader engineering organization to ensure smooth handoff of prototypes into production systems.
• Collaborate directly with product stakeholders and end-users to validate AI prototypes and gather feedback for successful delivery

What You Will Bring As a Machine Learning Engineer

• Minimum of 3+ years of experience in Machine Learning Engineering, AI Engineering, Data Science, or a similar role.
• Strong understanding of how large language models work: transformer architectures, attention mechanisms, tokenization, embeddings, and inference pipelines.
• Hands-on experience with cloud AI services, particularly AWS (Bedrock, SageMaker, Lambda).
• Practical experience building systems with embeddings and vector databases for semantic search or retrieval-augmented generation (RAG).
• Familiarity with agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI, or similar) and understanding of agent architectures including planning, memory, and tool use.
• Strong software engineering fundamentals: Python, REST APIs, Git, Docker, and CI/CD.
• Solid foundation in mathematics: linear algebra, probability, statistics, and optimization. Understanding of classical ML algorithms and when they apply.
• Bachelor’s degree in Computer Science, AI, Mathematics, Physics, or a related field.

Bonuses

• Master’s degree or PhD in a relevant field.
• Experience w