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Mission du poste
Freelance Machine Learning Engineer (Contract) – Belgium
Location: Belgium (Hybrid – 2 days per week onsite)
Contract Length: 6–12 Months
Rate: Competitive Market Rate
Start Date: ASAP
Client: Major International Banking & Financial Services Organisation
Interview Process: 2 Stages
About the Role
We are seeking an experienced Machine Learning Engineer to join a large-scale AI and Data Engineering programme within a leading banking organisation in Belgium.
This role sits at the intersection of Data Science, MLOps, Software Engineering, and Production Operations, ensuring machine learning solutions are successfully transitioned from experimentation to robust, scalable production environments.
The successful consultant will work closely with Data Scientists, Data Engineers, Infrastructure Teams, and Production Support teams to build, deploy, monitor, and optimise enterprise-grade AI solutions.
Key Responsibilities
Machine Learning Engineers contribute to Machine Learning projects by:
- Working with Data Scientists to define and develop target solutions with production constraints in mind.
- Selecting appropriate runtime infrastructure and serving models to meet business requirements, including:
- Data ingestion architectures
- API design and synchronicity
- Real-time and batch processing requirements
- High-volume data processing considerations
- Contributing to the automation of Machine Learning pipelines and deployment processes.
- Building and maintaining Docker images and virtualised environments.
- Developing unit, integration, and regression testing frameworks for ML applications.
- Supporting Data Scientists in the use of existing industrial AI platforms and CI/CD tooling.
- Supporting IT Production teams with environment setup, configuration, deployment, and operational readiness.
- Implementing best practices around model deployment, monitoring, governance, and lifecycle management.
- Collaborating across distributed technology environments and enterprise infrastructure platforms.
Required Skills & Experience
Essential
- Minimum 4 years' commercial experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
- Strong programming expertise in Python (4+ years).
- Experience with CI/CD pipelines, particularly GitLab CI/CD (4+ years).
- Strong understanding of:
- Containerisation and virtualisation technologies
- Machine Learning deployment architectures
- Production-grade software engineering practices
- Experience with:
- Kubernetes
- Docker
- PostgreSQL
- Code, model, and data versioning
- Package management and dependency management tools
- Experience deploying and maintaining machine learning solutions in production environments.
- Knowledge of AI development platforms and IDEs.
- Experience supporting operational and production teams.
Preferred
- Experience integrating systems across distributed platforms and mainframe environments.
- Knowledge of model optimisation and compression techniques.
- Experience with ELT/ETL tooling.
- Strong understanding of big data ecosystems, including Spark.
- Experience with data flow processing technologies.
- Exposure to data visualisation tools and reporting platforms.
- Experience within highly regulated environments such as banking, financial services, or insurance.
Desired Profile
- Strong communication and stakeholder management skills.
- Ability to bridge the gap between Data Science and Engineering teams.
- Comfortable working in complex enterprise environments.
- Proactive problem solver with a strong focus on scalability, reliability, and automation.
- Experience delivering business-critical AI and Machine Learning solutions.
Contract Details
- Role: Freelance Machine Learning Engineer
- Location: Belgium (Hybrid – 2 days onsite per week)
- Duration: 6–12 Month Initial Contract
- Rate: Competitive Market Rates
- Start Date: ASAP
- Interview Process: 2 Stages
- Industry: Banking & Financial Services
If you're an experienced Machine Learning Engineer with a strong background in MLOps, CI/CD, Kubernetes, and enterprise AI deployment, we'd love to hear from you.
