Machine Learning Engineer

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 with prompt engineering, context engineering, and LLM evaluation frameworks. Knowledge of MLOps practices: model monitoring, A/B testing, and deployment pipelines for AI features. Experience with computer vision or image/video processing (highly relevant to our DAM domain). Proficiency with AI-assisted coding tools and workflows (GitHub Copilot, Cursor, Claude Code, etc.). Familiarity with GDPR and data privacy considerations for AI systems in Europe. Experience working in a B2B SaaS or enterprise software environment. What You Will Bring As a Colleague A self-starter mentality. You thrive in an R&D environment with ambiguity and open-ended challenges. Intellectual curiosity and a genuine passion for AI, with a habit of staying current with the latest developments. The ability to connect the dots between mathematical theory, engineering impleme

Overview Bynder goes far beyond managing digital assets. Our AI-powered digital asset management platform enables teams to conquer the chaos of proliferating content, touch points, and relationships in order to thrive. With intuitive, AI-powered solutions that enhance content creation, simplify asset discovery, and maximize the value of every asset, we are the brand ally that unifies and transforms the creation and sharing of assets-inspiring teams, delighting customers, and elevating businesses. Join our global team of 600+ 'Byndies' and contribute to shaping the future of digital asset management As a leader in the industry, our AI capabilities empower over 1.4M users across 3,700+ organizations, including Spotify, Puma, Five Guys and Icelandair to work smarter with their content. With a commitment to innovation and a presence in seven offices worldwide, Bynder offers a dynamic environment where you can make a real impact. Ready to grow your career by helping the world's leading