Senior MLOps Platform Engineer with GenAI experience

We are building an AI-first platform that fuses multiple maritime data sources into a unified operational picture. As a MLOps Platform Engineer, you will build and own the infrastructure supporting ML models throughout their lifecycle.

• Design and implement systems for dataset and label management, including versioning and customer feedback integration
• Establish and maintain a model repository/registry with version control, lineage tracking, and local inference support
• Lead implementation of experiment tracking and monitoring solutions for data science and generative AI, focusing on evaluation, drift detection, and reproducibility
• Lead the deployment, lifecycle management, and continuous improvement of ML/DL models in production
• Own model serving and inference infrastructure, including autoscaling, A/B testing, canary deployments, and latency/cost optimization
• Enable generative AI capabilities by developing tagging tools, prompt management services, and LLM testing frameworks
• Drive operational excellence by improving tool deployment usability and establishing granular cost visibility across environments and projects
• Develop reusable components such as standardized data loaders, CI/CD pipelines, and automated model retraining workflows
• Collaborate with data scientists and platform engineers to productionize ML/DL models in public cloud environments

• At least 5 years of hands-on experience in MLOps / ML Platform Engineering (or equivalent ML Engineering experience with strong MLOps ownership)
• Experience collaborating closely with Data Scientists or ML Research teams to productionize machine learning models
• Strong Python programming skills
• Hands-on experience in containerization, CI/CD, and public cloud platforms (AWS, Azure, or GCP) for deploying, serving, and monitoring ML models
• Proficiency with dataset management, model versioning, experiment tracking, monitoring, and MLOps platforms (e.g. MLflow, SageMaker, or similar tools)
• Experience with machine learning frameworks (PyTorch or TensorFlow), big-data technologies (Apache Spark), and data stores such as PostgreSQL, MongoDB, and Redis
• Experience using AI-assisted development tools and adopting Generative AI and agentic workflows in day-to-day software development
• Java programming experience in production environments (Nice to have)

• 20 days of vacation leave per calendar year (plus official national holidays)
• Full accounting and legal support in all countries we operate
• Fully remote work model with a powerful workstation and co-working space
• Highly competitive package with yearly performance and compensation reviews