What we are looking for:

We’re looking for a skilled MLOps Engineer to join our team and help scale our machine learning infrastructure. You’ll play a key role in designing, deploying, and maintaining end-to-end ML pipelines that power impactful data-driven products. You’re someone who’s passionate about automation, and building systems that are fast, secure, and robust.

Your background enables you to bridge the gap between data science and production. In this role, you’ll work closely with cross-functional teams to version, test, deploy, and monitor models that support real-world and multi-tenant applications. You enjoy making things work seamlessly, from model training to serving at scale.

You’ll be part of a collaborative, agile team that values clean code, reproducibility, and observability. While you bring a strong foundation in modern MLOps practices, we’re also excited to support your continued learning as the field evolves.

What you'll be doing:

• Collaborate closely and support the team to make model training, development, and monitoring fast, scalable, and cost-efficient.
• Working with infrastructure as code technology to deploy, and manage robust MLOps solutions.
• Proactively suggesting and implementing improvements to our ways of working within and beyond the team.
• Stay up to date with the latest trends and technologies in MLOps, AI, and cloud computing, and drive continuous innovation throughout the organization.

Qualifications:

• Hand-on experience building multi-tenant AI and machine learning systems.
• A strong understanding of CI/CD pipelines and automation tools.
• Experience working with Kubernetes to orchestrate scalable, containerized ML workloads.
• Strong experience in cloud platforms (we use AWS) and cloud-native tools.
• Fluent in English, residing in Sweden

This is a full-time position with a preferred start date during Q2, based in our office at Birger Jarlsgatan 7, Stockholm.

Department

Machine Learning

Locations

Sthlm HQ

Remote status

Temporarily Remote

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