Machine Learning Engineer

What you will do

We are launching a greenfield innovation project aimed at enhancing the consumer search journey by introducing visual search capabilities within our mobile application. To explore feasibility, we're building a dedicated team to prototype and deliver a shippable MVP integrated into our existing technical landscape.

As an MLOps Engineer, you will play a critical role in enabling the deployment, scalability, and monitoring of machine learning models—particularly focused on image processing and computer vision.

You will:

• Design, build, and maintain robust ML deployment pipelines using CI/CD principles.
• Deploy and monitor ML models in production, ensuring reliability and scalability.
• Integrate models into a containerized environment (Docker) and orchestrate using Kubernetes.
• Work closely with mobile developers, backend engineers, and data scientists to support end-to-end delivery.
• Evaluate and implement model serving frameworks and deployment patterns.
• Ensure observability using monitoring and logging tools.

Client description:

Our client is a forward-thinking, data-driven company operating in the digital commerce space. Innovation is a core value, and this project reflects a strong commitment to continuously improve user experiences through advanced technology.

Work environment:

You will be part of the Search department, working in a newly formed, cross-functional product team that includes mobile developers, backend engineers, and data scientists. The environment encourages rapid prototyping, experimentation, and lean delivery cycles while integrating into a mature software ecosystem.

Expected results:

• Functional, production-ready ML pipelines that support visual search capabilities.
• Efficient and secure containerized deployments of ML models in a cloud environment.
• End-to-end observability of the deployed systems.
• Collaboration with team members to produce a prototype and MVP that meet business and technical standards.

What you’ll bring

Education:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.

Experience:

• Minimum of 5 years in MLOps or a similar role, including experience with deploying ML models in production settings.

Technical skills:

• Deep knowledge of ML deployment pipelines and CI/CD best practices
• Expertise with Docker and Kubernetes
• Hands-on experience with GCP preferred (AWS/Azure acceptable)
• Familiarity with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KFServing, or similar)
• Experience with observability tools (e.g., Prometheus, Grafana, ELK, or similar)

Competencies:

• Strong communication and documentation abilities
• Agile mindset and ability to thrive in iterative development environments
• Ability to meet deadlines under pressure
• Team player with a proactive and problem-solving attitude

Languages:

• Fluency in English (spoken and written)
• Dutch is a plus, but not required

This a 12 month contract + extension