Full Stack AI/ML Engineer

Startup Atlas; Oost-Vlaanderen; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

CHILI publish, a Belgium-based cloud platform, seeks a Full Stack AI/ML Engineer to turn ambitious ideas into production-grade features. You will work at the intersection of ML, backend systems, and product, delivering user-facing AI capabilities at scale.

You'll own Vector DB and RAG architectures, design scalable ML pipelines, and drive MLOps practices across the team, collaborating closely with Product and Engineering in a hybrid, Belgium-based setup.

Qualifications

• At least 2 years of production experience building and operating Vector Databases and RAG architectures at scale.
• Hands-on experience with MLOps: deployment, versioning, monitoring, CI/CD for ML, and infrastructure tooling (e.g. MLflow, Weights & Biases, SageMaker, or similar).
• Strong full-stack development ability - you can build the API layer, hook it up to a frontend, and know enough about UX to make it intuitive for clients. You feel comfortable building API’s in Node (TypeScript) and train, evaluate, run scripts and models in Python.
• A solid grasp of LLM ecosystems - prompt engineering, fine-tuning trade-offs, embedding models, and how to build reliable, observable AI features in production, considering cost and performance.
• The ability to communicate clearly about functional and technical aspects to both engineers and non-engineers.

Responsibilities

• Architect and maintain Vector DB solutions and RAG systems that power intelligent search, content suggestions, and automation features in our platform.
• Design and build scalable ML pipelines that go from experimentation to production without losing rigor or reliability.
• Bridge the gap between models and product - you won't just train models, you'll wire them into real user-facing features and backend services, end to end.
• Own MLOps practices across the team: versioning, monitoring, deployment pipelines, model drift detection, and continuous evaluation.
• Collaborate closely with product and engineering to translate fuzzy business problems into well-defined ML problems - and ship solutions that actually move the needle.
• Stay current with the fast-moving AI landscape and bring well-considered ideas on where we should invest next.

Skills

Vector Databases

RAG architectures

MLOps

Full-stack development

Node.js/TypeScript

Python

LLM ecosystems

Clear communication

Tools

MLflow

Weights & Biases

SageMaker

Weaviate

PGVector

Pinecone

Qdrant

Job description

Automate your Visual Content. Stop wasting time on manual graphic production. With CHILI GraFx, users generate localized, brand-proofed campaign assets on the fly. Controlled centrally, embraced locally.

Join CHILI publish to develop production-grade AI features for their cloud platform, focusing on machine learning, backend systems, and product integration. The role involves architecting Vector DB solutions, building scalable ML pipelines, and owning MLOps practices in a collaborative, international team based in Belgium.

Job Description

Full Stack AI/ML Engineer

• Hybrid
• Delivery

Join us to turn AI ideas into real product features used by our customers worldwide. Work with a curious team building smarter tools for creative automation.

Think you've got the talent? Let's talk.

At CHILI publish, we build a cloud platform that helps brands and agencies create, automate, and scale digital content with ease. AI and machine learning are becoming central to how we help our customers work smarter - from intelligent content automation to smart templating, recommendations, and beyond.

We're not hiring for a checkbox. We're looking for someone who wants to shape how AI gets built into a real product, used by real people, at scale. Closely working together with your team members and directly with our Product team.

What you'll be doing

You'll work at the intersection of machine learning, backend systems, and product - turning ambitious ideas into production-grade AI features that our customers rely on every day.

• Architect and maintain Vector DB solutions and RAG systems that power intelligent search, content suggestions, and automation features in our platform.
• Design and build scalable ML pipelines that go from experimentation to production without losing rigor or reliability.
• Bridge the gap between models and product - you won't just train models, you'll wire them into real user-facing features and backend services, end to end.
• Own MLOps practices across the team: versioning, monitoring, deployment pipelines, model drift detection, and continuous evaluation.
• Collaborate closely with product and engineering to translate fuzzy business problems into well-defined ML problems - and ship solutions that actually move the needle.
• Stay current with the fast-moving AI landscape and bring well-considered ideas on where we should invest next.

Who you are

• You take ownership - not just of your code, but of outcomes. If something isn't working, you don't wait to be told.
• You're relentlessly curious - you follow the latest AI developments not because you have to, but because you genuinely want to know what's possible.
• You balance speed with thoughtfulness - you can ship fast without cutting corners that matter.
• You thrive in a collaborative, international team where English is the working language and diverse perspectives are genuinely valued.

How we work

• We're an international team headquartered in Belgium. We move fast, but thoughtfully. We offer flexible and remote-friendly work arrangements, while expecting regular presence at our Belgian HQ. For this role we are specifically searching for a Belgium based profile (or able to be present weekly in our HQ) since regular office meetings are expected.
• Salary and overall package are competitive and discussed transparently from the first screening call.

Curious?

If this resonates, we'd love to connect. Send us your CV and a short cover letter - tell us about an AI/ML system you're proud of building, and where you see yourself making the biggest impact at CHILI publish.

Job requirements

Must-haves:

• At least 2 years of production experience building and operating Vector Databases (e.g. PGVector, Pinecone, Weaviate, Qdrant) and RAG architectures at scale.
• Hands-on experience with MLOps: model deployment, versioning, monitoring, CI/CD for ML, and infrastructure tooling (e.g. MLflow, Weights & Biases, SageMaker, or similar).
• Strong full-stack development ability - you can build the API layer, hook it up to a frontend, and know enough about UX to make it intuitive for clients. You feel comfortable building API’s in Node (TypeScript) and train, evaluate, run scripts and models in Python.
• A solid grasp of LLM ecosystems - prompt engineering, fine-tuning trade-offs, embedding models, and how to build reliable, observable AI features in production, considering cost and performance.
• The ability to communicate clearly about functional and technical aspects to both engineers and non-engineers.

Nice-to-haves:

• Background in data science or applied ML research - familiarity with model evaluation, experimentation design, and statistical thinking.
• Experience with cloud-native ML infrastructure (Azure, AWS or GCP ML- and DevOps tooling).
• Exposure to content generation, document understanding, or creative (mar) tech - the domain we operate in.