Machine Learning Ops Engineer – Personalization (m|w|d)

About This Opportunity

We are representing a confidential e-commerce technology organization in their search for a Machine Learning Ops Engineer focused on personalization initiatives. This role sits at the intersection of cloud infrastructure, ML engineering, and product development, working to scale intelligent systems that serve millions of users.

Our client is building the next generation of their platform, transforming how users discover and engage with products through data-driven personalization. You'll join a cross-functional team working on one of the company's most strategic initiatives.

Responsibilities

• Build and operate scalable machine learning infrastructure on AWS
• Design, develop and deploy production-ready ML pipelines covering training, inference, monitoring and automated retraining
• Bring machine learning models into production for personalized recommendations, discovery feeds, search ranking and related use cases
• Build cloud-native infrastructure using Infrastructure as Code and modern CI/CD practices
• Ensure high availability, observability and operational excellence of ML systems
• Collaborate closely with Software Engineers, Data Scientists, Product Managers and UX Designers to continuously improve personalized customer experiences
• Work throughout the entire machine learning lifecycle, focusing on infrastructure, ML pipelines and operational tooling that enable models to run reliably and scale efficiently

What We're Looking For

• At least three years of professional experience as a Machine Learning Engineer, Software Engineer or Cloud Engineer, including exposure to production ML systems
• Strong Python programming skills and experience building cloud-native solutions, ideally on AWS
• Hands-on experience with Infrastructure as Code, such as Terraform or CDK, as well as CI/CD pipelines
• Experience with ML platforms such as AWS SageMaker or comparable technologies, including deploying, operating and monitoring models in production
• Solid knowledge of machine learning concepts and model evaluation
• Experience with recommendation systems, search, ranking, vector search or embeddings is a strong plus
• Strong communication and collaboration skills across technical and non-technical teams
• Excellent written and spoken English; German is a plus

How We Work With You

Candidates apply directly through Get A Job.ai. Our talent team will conduct an initial screening to understand your background and match you with the right opportunity. Once aligned, we submit your profile to our client for consideration. Please do not contact the client directly—we manage all communications to ensure the best possible experience for you throughout the hiring process.

Pay

Compensation details will be discussed during the screening process based on your experience and the client's budget for this role.

Equal Opportunity

Get A Job.ai is committed to creating an inclusive recruiting experience for all candidates regardless of race, color, religion, sex, national origin, age, disability, or veteran status.