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- Help design, build and continuously improve the clients online platform.
- Research, suggest and implement new technology solutions following best practices/standards.
- Take responsibility for the resiliency and availability of different products.
- Be a productive member of the team.
- AI/ML Senior Engineer to join our growing ML Engineering team.
- Collaborate closely with data scientists, engineers, and product managers to design, deploy, and operate production-grade machine learning systems that power critical services across our Digital and Retail platforms.
- This position has a strong focus on MLOps and ML platform development, helping scale and maintain reliable, end-to-end ML workflows using modern cloud-native infrastructure and tools.
- Design, build, and maintain ML pipelines for model training, validation, deployment, and monitoring.
- Enable scalable ML solutions for use cases such as recommendation systems, forecasting, and intelligent automation.
- Develop and deploy production-ready services using tools such as Airflow, Azure ML, and FastAPI.
- Automate model build and deployment workflows using CI/CD pipelines (GitHub Actions, Azure DevOps).
- Ensure reliability, observability, and performance of the ML platform.
- Collaborate with data scientists to productionize research models and code into scalable services.
- Implement monitoring, alerting, and model drift detection using tools like Azure Monitor, New Relic, Grafana, and custom logging frameworks.
- Continuously improve and manage cloud infrastructure using Terraform, Docker, and Fargate.
- Proven experience in ML Engineering, MLOps, DevOps, or Data Engineering with exposure to the full ML lifecycle.
- Hands-on experience building and maintaining ML workflows and pipelines.
- Strong proficiency in Python, with experience using MLflow, Scikit-learn, or PyTorch.
- Experience with cloud platforms, particularly Azure and/or AWS.
- Solid understanding of containerization (Docker) and orchestration technologies such as Kubernetes.
- Hands-on exposure to CI/CD tools (GitHub Actions, Azure DevOps) and Infrastructure as Code (Terraform).
- Strong collaboration and communication skills, with the ability to work in cross-functional teams.
- Languages: Python (primary), SQL, Bash
- Cloud Platforms: Azure, AWS
- ML & Workflow Tools: MLflow, Azure ML, Airflow
- APIs & Services: FastAPI, Azure Functions
- Data Platforms: Snowflake, Delta Lake, Redis, Azure Data Lake
- Infrastructure & DevOps: Docker, Fargate, Terraform, GitHub Actions, Azure DevOps
- Monitoring & Observability: Grafana, Azure Monitor, New Relic
- Experience working with enterprise data platforms such as Snowflake or Azure Data Lake.
- Experience deploying ML models as APIs or microservices.
- Strong understanding of model performance tracking, monitoring, and observability best practices.
- Familiarity with orchestration tools such as Airflow or Azure Data Factory.
- A challenging, innovating environment.
- Opportunities for learning where needed.
Key Skills
Ranked by relevance
docker
devops
cloud
terraform
grafana
python
mlflow
mlops
cicd
infrastructure as code
containerization
machine learning
fastapi
redis
sql
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Login to Apply
- Posted
- Jan 12, 2026
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Amsterdam
- Company
- GeekSoft Consulting
Industries
IT Services
IT Consulting
Categories
Information Technology
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Senior Data & Machine Learning Engineer (all genders)
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