Machine Learning Engineer

We’re looking for a Machine Learning Engineer who can build the brains of an AI solution, but who is equally comfortable building the body too. This is not a research role - you will design, build, and own AI-powered systems end-to-end, working closely with clients, a Delivery Manager, and an AI Consultant to translate real business needs into production solutions. If you thrive at the intersection of applied AI, solid engineering, and client impact, this is your role.

• Design, build, and maintain AI-powered backend services - primarily Python - that run reliably in production.
• Own the full lifecycle of AI features: from scoping and prototype through to deployment and monitoring.
• Contribute across the stack where needed - backend is your core, but you’re comfortable touching APIs, data pipelines, and lightweight frontend integration when the project calls for it.
• Work closely with clients alongside the AI Consultant and Delivery Manager - understand their needs, translate them into technical solutions, and communicate clearly on progress and trade-offs.
• Uphold engineering best practices: code quality, performance, scalability, and security.

• An engineer with 3–5 years of experience building production systems, with a strong foundation in applied AI.
• Proactive and action-oriented - you seek ownership and don’t wait to be told what to do.
• Comfortable working in client environments: you ask good questions, listen well, and can explain technical decisions without jargon.
• Curious and pragmatic - you keep up with the fast-moving AI landscape and know when to reach for a new tool vs. when to keep it simple.

• Proven experience with modern genAI design patterns including RAG and agent orchestration.
• Strong Python backend development skills (FastAPI or Django experience preferred).
• Experience with chatbot or conversational AI development and vector databases (e.g. Pinecone, Weaviate, pgvector).
• Experience with at least one GenAI orchestration framework (e.g. Lang Chain, Llama Index, Azure AI Foundry, AWS Bedrock etc.).
• Familiarity with agentic AI patterns and multi-agent system design.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and containerisation (Docker, Kubernetes).
• Bachelor’s or Master’s in Computer Science, AI, or a related technical field.

• Experience with Dev Ops practices: CI/CD, infrastructure as code, monitoring and observability.
• Frontend exposure - enough to integrate AI features into a UI or collaborate effectively with frontend developers. Preferably React.
• Familiarity with image generation models (Control Net, LoRA, diffusion architectures).
• Experience in a consultancy or agency environment.

• Office lunches, snacks & drinks
• Youwe Academy & a learning budget
• Flexible hours & hybrid work options
• 4 weeks remote work per year from anywhere
• Loyalty days: extra vacation after 3 & 6 years
• Bike plan: 40% discount on commuting products