MLOps Platform Engineer

One of Nordic Investin’s partner companies is looking for an MLOps Platform Engineer, with Nordic Investin leading the recruitment process. You want data scientists to experiment freely while production models remain reproducible, observable and governable. The partner is scaling machine learning across several teams and needs a common platform for training, deployment and monitoring. You will build the paved paths that connect experiments with reliable services. The partner wants data and AI work that can be operated, explained and improved after launch. Provenance, quality, access and evaluation belong in the solution from the beginning. How you will work You will work with engineers, analysts and domain specialists who look at the same information from different angles. The partner expects assumptions, datasets and evaluation methods to be visible. Solutions should be designed for repeatable delivery, monitored use and responsible change after deployment. As a senior colleague, you will own substantial outcomes and help others make stronger decisions. You are expected to recognise risk early, communicate it without drama and move work forward with practical alternatives. The role still includes hands on delivery; seniority here means broader judgement, not distance from the work. What you will do Create reusable training and inference infrastructure. Automate model packaging, validation and deployment. Build feature, registry and experiment tracking integrations. Implement monitoring for data and model behaviour. Manage compute, access and cost controls. Support teams adopting the platform through examples and documentation. What you will bring Production platform, DevOps or machine learning engineering experience. Strong Python and cloud infrastructure knowledge. Containers, Kubernetes and CI CD. Experience with ML lifecycle tools such as MLflow or managed cloud services. Infrastructure as code and observability skills. Ability to design for