As an MLOps Engineer, you are an integral part of our consulting team and work closely with clients to implement, operate, and optimize ML platforms.
With your expertise, you ensure the successful deployment and management of machine learning models by leveraging the latest advances in automation, monitoring, and scalability.
You understand and consolidate the MLOps requirements of our clients.
As an MLOps Engineer, you can design and present solutions and meet requirements, including architectures and best practices.
You can deploy, maintain, and extend functionality as well as support data science use cases and ML models with ease.
Responsible for the successful deployment and management of machine learning models and the underlying platform.
Plan, develop, test, automate, document, and maintain CI/CD pipelines.
Utilize the latest developments in automation, monitoring, and scalability.

At least three years of experience as an MLOps, DevOps, or Data Engineer building and operating production data infrastructures.
Confident experience with cloud environments (AWS/Azure), Infrastructure-as-Code (Terraform), container orchestration (Docker, Kubernetes), and workflow tools such as Airflow.
A holistic understanding of the machine learning lifecycle, complemented by strong Python skills and practical experience with Kubeflow or MLflow.
Implementing efficient CI/CD pipelines as well as monitoring, alerting, and incident management for production systems are part of your established routines.
With a passion for mentoring, you develop the team professionally and establish sustainable best practices.
You demonstrate an analytical, independent working style and are fluent in German and English.

Work–life balance: trust-based working hours with flexible scheduling, a hybrid work model, and the option for workation — the possibility to work from within the EU.
Unique team atmosphere, flat hierarchies up to our CEO Alex, and an open feedback culture; annual team workshops at our Data.Castle in the Zillertal; a lived Data.Musketeer principle — “one for all, all for one!”; our [at] Buddy program for better networking; regular professional and social events; dog-friendly offices.
Intensive onboarding and induction process, a personal development plan, and individual training opportunities; a diverse workshop and training offering within the Data.Academy provided by our experienced Data.Musketeers and external providers; career paths in leadership, project management, and as a subject-matter expert.
Childcare subsidy, company pension plan with a 20% employer contribution, numerous corporate benefits and employee offers (e.g., for events and travel), starter credit for our internal merchandise shop, and a competitive salary with variable components.
Mental health & wellbeing support including coaching and meditation via nilo.health; fitness and yoga rooms in the Munich office; regular employee surveys; EGYM Well Pass membership with a Plus1 option; bike leasing via JobRad after the probation period; internal groups for sports activities; free hot and cold beverages and fresh fruit in the office; roof terrace (grill).

Senior MLOps Engineer – m/f/d

Key skills