AI/ML Engineer

pCraftzing and Sagacify are looking for an bAI/ML Engineer /b 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. /p pDo 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. /p pWe're on the lookout for an bAI/ML Engineer /b 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. /p pIn 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. /p h3What you'll do /h3 ul liUnderstand clients' business needs and translate them into clear, feasible end-to-end AI solutions /li liAct as a trusted point of contact for clients throughout the project, from scoping to delivery /li liRun discovery sessions and technical workshops with business and technical stakeholders /li liDesign and build AI solutions combining LLMs, vector databases, APIs, orchestration layers and user interfaces /li liDevelop agents and RAG pipelines connecting client data to LLMs for grounded, reliable answers /li liPerform prompt and context engineering to improve output quality and reduce hallucinations /li liBuild, train and evaluate classical ML models (classification, regression, forecasting, clustering) when they are the best fit for the problem /li liHandle the data side: gathering, cleaning, validating data quality and feature engineering /li liEvaluate solutions rigorously, using ML metrics, generative AI metrics and production monitoring (quality, drift, costs) /li liDeploy solutions to the cloud with attention to security, reliability and cost efficiency, including versioning and reproducibility of models and data /li liPresent and explain AI concepts, trade-offs and results to non-technical audiences /li liSupport sales in qualifying opportunities, estimating effort and writing proposals /li liContribute to demos, proofs of concept and internal knowledge sharing /li /ul pYou stay in the code, you stay close to the client, and you keep learning as you go. /p h3Who we're looking for /h3 ul liYou hold a Master's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics or a related field /li liYou have 2 to 5 years of experience in AI/ML engineering or related fields /li liYou're proficient in Python and software development best practices /li liYou have strong machine learning fundamentals: supervised and unsupervised learning, feature engineering, model validation and the statistics behind them /li liYou have hands-on experience with the Python data and ML stack: Pandas, NumPy, Scikit-learn and PyTorch (or TensorFlow) /li liYou have a solid understanding of LLM fundamentals: Transformers, generation parameters, RAG and fine-tuning approaches /li liYou have hands-on experience with tools such as the OpenAI API, Hugging Face, LangChain/LangGraph, FastAPI and Docker /li liYou're comfortable working with data in SQL databases /li liYou're a natural consultant: you listen, ask the right questions and see the business behind the technical problem /li liYou're comfortable presenting to clients and explaining complex topics simply /li liYou have strong problem-solving ability and a pragmatic, solution-oriented mindset /li liYou have a team spirit and enjoy collaborating across multiple roles /li liYou're autonomous, curious, and quick to learn new tools /li liYou can communicate fluently in English and French or Dutch /li /ul h3Bonus points : /h3 ul liExperience with a major cloud provider (AWS, Azure or GCP) /li liFamiliarity with MLOps practices: CI/CD, model and data versioning (MLflow, DVC), monitoring, Kubernetes /li liExperience in one of our other focus domains: NLP, Computer Vision or time series /li liExperience with gradient boosting libraries (XGBoost, LightGBM) /li liPrevious experience in a client-facing role /liliExperience contributing to proposals, pre-sales or client workshops /li liAI-native engineering workflows: hands-on experience with AI coding agents and AI-assisted development environments (Cursor, Claude Code, Windsurf, Copilot, etc