Machine Learning Engineer

Role overview

Join Bynder AI Labs, the AI innovation team responsible for researching, prototyping, and delivering next-generation AI capabilities for Bynder’s platform. As a Machine Learning Engineer, you will design, build, deploy, and evaluate AI-powered features in collaboration with product stakeholders and end-users.

Responsibilities

• Design, build, and deploy AI-powered features for Bynder’s DAM platform, focusing on:
  • Content discoverability
  • Automation
  • Intelligent workflows
• Architect and implement solutions using AWS AI services and LLM APIs:
  • Bedrock, SageMaker, Lambda
  • Large language model APIs
• Collaborate with product stakeholders and end-users to validate prototypes, collect feedback, and drive successful delivery

Requirements

• Agentic AI framework familiarity (e.g., LangChain, LangGraph, CrewAI, or similar) and understanding of agent architectures (planning, memory, tool use)
• Strong math foundation (linear algebra, probability, statistics, optimization) and knowledge of classical ML algorithms
• Software engineering fundamentals:
  • Python, REST APIs, Git, Docker, CI/CD
• Experience building embeddings and using vector databases for:
  • semantic search
  • RAG (Retrieval-Augmented Generation)
• Strong understanding of LLMs (transformer architectures, attention mechanisms, tokenization, embeddings, inference pipelines)
• Hands-on experience with AWS AI services (Bedrock, SageMaker, Lambda)
• 3+ years of experience in Machine Learning Engineering / AI Engineering / Data Science (or similar)
• Experience with prompt engineering, context engineering, and LLM evaluation frameworks
• Experience in B2B SaaS or enterprise software environments
• Familiarity with GDPR and European data privacy considerations for AI
• Communication skills in English; ability to explain complex AI concepts to non-technical stakeholders
• Responsible AI mindset (bias, fairness, transparency, real-world impact)
• Growth mindset, self-starter attitude, and ability to thrive in an R&D environment

Nice to have

• Master’s degree or PhD in a relevant field
• Experience with computer vision or image/video processing (relevant to DAM)
• MLOps experience (model monitoring, A/B testing, deployment pipelines)
• Experience with AI-assisted coding tools/workflows (e.g., GitHub Copilot, Cursor, Claude Code)