Machine Learning Engineer

Discai; Vlaams-Brabant; Sur place; EUR 65 000 - 90 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Permanent contract

Collaborative team

Résumé du poste

Discai, a fintech company, seeks a Machine Learning Engineer to bridge data science and software engineering, turning prototypes into reliable production systems.

You will build scalable ML pipelines, optimize performance and cost, monitor models, and collaborate with data scientists, engineers and cloud specialists.

Based in Belgium, you will contribute to AI-powered solutions for financial crime prevention and stay ahead with best practices in MLOps.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering or related field.
• Min 4 years experience in ML engineering, data science or similar role.
• Proven track record of operationalising ML solutions.
• Strong Python programming skills.
• Solid SQL knowledge.
• Experience with ML libraries and data processing tools such as scikit-learn, SciPy, SHAP, Polars.

Responsabilités

• Transform machine learning prototypes into scalable, production-ready solutions.
• Design, develop and maintain end-to-end ML pipelines.
• Optimize performance, reliability and cost-efficiency of ML solutions.
• Strengthen and automate model monitoring capabilities for quality.
• Develop and automate testing strategies for ML pipelines.
• Collaborate with data scientists to build scalable ML solutions using MLOps.
• Work with data engineers to ensure data pipeline integration.
• Maintain CI/CD workflows and automated quality controls.
• Document architecture decisions and implementation choices clearly.

Connaissances

Python

SQL

MLOps

CI/CD

Cloud AWS

Docker

Data pipelines

Stakeholder comms

Formation

Bachelor's or Master's in CS/DS/Engineering

Outils

scikit-learn

SciPy

SHAP

Polars

MLflow

SageMaker

GitHub

Description du poste

What does this job involve?

Machine learning models only create real value when they are reliable, scalable and ready for production. That's where you come in. As a Machine Learning Engineer at Discai, you bridge the gap between data science and software engineering.

You will contribute to the development of our AI-powered solutions and ensure that machine learning models evolve from proof of concept to robust production systems. In this role, you combine machine learning expertise with strong software engineering and MLOps practices.

You will join an innovative fintech company where AI, data and technology are at the heart of everything we do. Working alongside data scientists, software engineers and cloud specialists, you will help build scalable solutions that support financial institutions in the fight against financial crime.

What do we expect from you?

• You transform machine learning prototypes into scalable, production-ready solutions.
• You design, develop and maintain end-to-end machine learning pipelines.
• You optimise the performance, reliability and cost-efficiency of ML solutions.
• You strengthen and automate model monitoring capabilities to ensure model quality and performance.
• You develop and automate testing strategies for machine learning pipelines.
• You collaborate closely with data scientists to build scalable solutions using MLOps best practices.
• You work with data engineers to ensure seamless integration of data pipelines.
• You maintain and improve CI/CD workflows and automated quality controls.
• You document architecture decisions, technical designs and implementation choices in a clear and structured way.

Please note that this role requires you to be based in Belgium.

Your strengths?

• You hold a Bachelor's or Master's degree in Computer Science, Data Science, Engineering or a related field.
• You have at least four years of experience in machine learning engineering, data science or a similar role.
• You have a proven track record of operationalising machine learning solutions and transforming prototypes into production systems.
• You have strong programming skills in Python.
• You have solid SQL knowledge.
• You are experienced with widely used machine learning and data processing libraries such as scikit-learn, SciPy, SHAP and Polars.
• Experience with MLflow or similar tools for experiment tracking and model registry is an asset.
• You have experience working with cloud platforms and production environments, preferably within AWS.
• You are familiar with orchestration tools such as AWS SageMaker Pipelines or equivalent solutions.
• Knowledge of Docker, CI/CD practices, GitHub and software design principles such as SOLID and clean coding is a plus.
• You communicate effectively with both technical and non-technical stakeholders.
• You have a strong analytical mindset and are passionate about building scalable and maintainable solutions.
• You are eager to learn and stay up to date with emerging technologies and industry trends.
• You adopt a security-conscious approach when handling sensitive data.

What can we offer you?

• The opportunity to join an innovative fintech company developing AI-powered solutions for financial institutions.
• Collaboration with experienced data scientists, machine learning engineers, software developers and cloud specialists.
• The chance to build AI solutions that have a direct impact on customers and the market.
• A working environment where innovation, autonomy and ownership are encouraged.
• Continuous learning and development opportunities through training, coaching and challenging projects.
• The opportunity to help shape the future of our products and technology landscape.
• A flexible working environment where collaboration, initiative and knowledge sharing are highly valued.
• A permanent contract, a competitive salary and an attractive package of additional benefits.

Think you could be a great fit?