AI/ML Engineer

JobLoom; Sint-Pieters-Woluwe; Hybride; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Snacks & coffee

Hybrid working culture

Health insurance & group life

Mobility budget

Résumé du poste

Sagacify, part of Craftzing, seeks an AI/ML Engineer who blends hands-on AI work with client collaboration. You’ll work on LLM-based apps, agents and RAG pipelines, while applying classical ML methods when suitable.

You’ll select the right tool for each problem and focus on business outcomes. You sit at the intersection of clients, business and engineering, reporting to the Head of ML and collaborating with Sagacify and Craftzing delivery and sales teams.

Qualifications

• Master's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics or a related field.
• 2–5 years of experience in AI/ML engineering or related fields.
• Proficient in Python and software development best practices.
• Solid ML fundamentals: supervised/unsupervised learning, feature engineering, model validation.

Responsabilités

• Understand clients' business needs and translate them into end‑to‑end AI solutions.
• Act as a trusted client contact from scoping to delivery.
• Run discovery sessions and technical workshops with stakeholders.
• Design and build AI solutions with LLMs, vector DBs, APIs and orchestration layers.
• Develop agents and RAG pipelines integrating client data with LLMs.
• Perform prompt/context engineering to improve outputs and reduce hallucinations.
• Build, train and evaluate classical ML models when appropriate.
• Handle data gathering, cleaning, validating, feature engineering.
• Evaluate solutions with ML metrics, AI metrics and production monitoring.
• Deploy solutions to the cloud with attention to security and cost.
• Present AI concepts and results to non-technical audiences.
• Support sales in qualifying opportunities and writing proposals.
• Contribute to demos, proofs of concept and knowledge sharing.

Connaissances

Python

ML fundamentals

LLM/Generative AI

Client collaboration

Prototyping/ML pipelines

DevOps basics

Communication

English fluency

Formation

Master's degree in CS/Engineering/Data Science

Outils

OpenAI API

Hugging Face

LangChain/LangGraph

FastAPI

Docker

Description du poste

Want to create a positive impact through AI?

Craftzing and Sagacify are looking for an AI/ML Engineer who is as comfortable in a client workshop as in a codebase. Someone who does not see understanding a business problem and building the AI system that solves it as two separate jobs, but as two things that make each other better.

Do you get energy from turning a client's fuzzy challenge into a working AI solution, whether that's an LLM-powered assistant or a well-tuned predictive model, and then explaining clearly why it works? Then you will probably feel right at home here.

Your Role

We're on the lookout for an AI/ML Engineer who bridges hands‑on AI engineering and client collaboration. Someone who loves getting hands‑on with LLMs, agents and RAG pipelines, has solid roots in classical machine learning, and cares just as much about the client's business outcome as about the technical solution itself. In this role, you'll help clients identify where AI creates real value, then design, build and deliver production‑grade solutions, with a strong focus on generative AI and LLM‑based applications, while picking the right tool for each problem, from a gradient‑boosted model to a multi‑agent system.

In this role you sit at the intersection of clients, business and engineering, working across teams and disciplines. You'll report to the Head of ML at Sagacify and collaborate with the wider Sagacify and Craftzing delivery and sales organisation.

What You'll Do

• Understand clients' business needs and translate them into clear, feasible end‑to‑end AI solutions
• Act as a trusted point of contact for clients throughout the project, from scoping to delivery
• Run discovery sessions and technical workshops with business and technical stakeholders
• Design and build AI solutions combining LLMs, vector databases, APIs, orchestration layers and user interfaces
• Develop agents and RAG pipelines connecting client data to LLMs for grounded, reliable answers
• Perform prompt and context engineering to improve output quality and reduce hallucinations
• Build, train and evaluate classical ML models (classification, regression, forecasting, clustering) when they are the best fit for the problem
• Handle the data side: gathering, cleaning, validating data quality and feature engineering
• Evaluate solutions rigorously, using ML metrics, generative AI metrics and production monitoring (quality, drift, costs)
• Deploy solutions to the cloud with attention to security, reliability and cost efficiency, including versioning and reproducibility of models and data
• Present and explain AI concepts, trade‑offs and results to non‑technical audiences
• Support sales in qualifying opportunities, estimating effort and writing proposals
• Contribute to demos, proofs of concept and internal knowledge sharing

You stay in the code, you stay close to the client, and you keep learning as you go.

Who We're Looking For

• You hold a Master's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics or a related field
• You have 2 to 5 years of experience in AI/ML engineering or related fields
• You're proficient in Python and software development best practices
• You have strong machine learning fundamentals: supervised and unsupervised learning, feature engineering, model validation and the statistics behind them
• You have hands‑on experience with the Python data and ML stack: Pandas, NumPy, Scikit‑learn and PyTorch (or TensorFlow)
• You have a solid understanding of LLM fundamentals: Transformers, generation parameters, RAG and fine‑tuning approaches
• You have hands‑on experience with tools such as the OpenAI API, Hugging Face, LangChain/LangGraph, FastAPI and Docker
• You're comfortable working with data in SQL databases
• You're a natural consultant: you listen, ask the right questions and see the business behind the technical problem
• You're comfortable presenting to clients and explaining complex topics simply
• You have strong problem‑solving ability and a pragmatic, solution‑oriented mindset
• You have a team spirit and enjoy collaborating across multiple roles
• You're autonomous, curious, and quick to learn new tools
• You can communicate fluently in English and French or Dutch

Bonus points

• Experience with a major cloud provider (AWS, Azure or GCP)
• Familiarity with MLOps practices: CI/CD, model and data versioning (MLflow, DVC), monitoring, Kubernetes
• Experience in one of our other focus domains: NLP, Computer Vision or time series
• Experience with gradient boosting libraries (XGBoost, LightGBM)
• Previous experience in a client‑facing role
• Experience contributing to proposals, pre‑sales or client workshops
• AI‑native engineering workflows: hands‑on experience with AI coding agents and AI‑assisted development environments (Cursor, Claude Code, Windsurf, Copilot, etc.)

Don’t worry if you don’t tick every single box, what matters most is the right mindset and a drive to learn. If you think we’re a match, we’d love to hear from you.

Why You Will Love Working With Us

Sagacify is part of Craftzing, and together we build AI solutions that create lasting impact for our clients. You will be part of a team of enthusiasts who love to learn, continuously develop new skills and fast‑track our customers' AI journey across various industries.

At Craftzing and Sagacify, you get the trust and space to do your best work - in a human‑sized environment with real team spirit, flexible working and room to take ownership.

• Snacks, fruits and unlimited coffee
• Net allowances, hospitalisation and group insurance
• Hybrid and flexible working culture
• Car & fuel or mobility budget
• Pleasant working environment
• Teambuildings and yearly holiday retreat

Recruiting process

• Interview with the Head of Talent & Culture and the Tech Lead
• Technical test
• Meeting with the team (to discover the reality of the position)
• Final interview & Offer