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

Jackalope Digital LLC; Berlin; Hybrid; EUR 70.000 - 110.000; Vollzeit

Benefits dieser Stelle

Office in Berlin

Free organic breakfast

Free lunch

Coffee & beverages

Rooftop terrace

Counseling services

Job bike/Deutschlandticket

Fitness options

Team events

Zusammenfassung

idealo is seeking a Machine Learning Engineer (m|f|x) to design and operate cloud-native ML infrastructure in Berlin. You will work with data scientists to deploy pipelines for personalised recommendations, enhanced discovery, and search ranking, ensuring reliability and scalability in production.

You will collaborate with cross-functional teams to continuously improve user experiences through ML-driven personalization and robust CI/CD practices.

Qualifikationen

• Three years of professional experience in ML/Cloud/Software roles including production ML systems.
• Strong Python programming skills and cloud-native solutions on AWS.
• Hands-on experience with Infrastructure as Code (Terraform or CDK) and CI/CD pipelines.
• Experience with ML platforms such as AWS SageMaker, including deploying and monitoring models in production.
• Knowledge of recommender systems, search, ranking, or embeddings is a plus.
• Strong communication and collaboration skills; English required, German is a plus.

Aufgaben

• Build and operate scalable ML infrastructure on AWS.
• Design, develop and deploy production-ready ML pipelines (training, inference, monitoring, retraining).
• Deploy ML models for personalized recommendations, discovery feeds, search ranking and related use cases.
• Build cloud-native infrastructure using IaC and modern CI/CD practices.
• Ensure high availability, observability and operational excellence of ML systems.
• Collaborate with Software Engineers, Data Scientists, PMs and UX Designers to improve personalization.

Kenntnisse

Python

English

German

Cloud architecture

Recommendation systems

CI/CD

Tools

AWS SageMaker

Terraform

CDK

Jobbeschreibung

Everyone at idealo bases decisions on data. Our vision is to transform idealo from a transactional price comparison platform into a personalised shopping companion that inspires users throughout their entire product discovery journey.

To make this vision a reality, we are looking for a Machine Learning Engineer (m|f|x) who is passionate about building scalable, cloud-native machine learning systems. Working in a cross-functional team alongside Product Managers, UX Designers, Software Engineers and Data Scientists, you will help create personalised experiences that make shopping more relevant, engaging and inspiring for millions of users.

About your new role

You will help shape one of idealo's most strategic product initiatives: Personalisation.

You will work closely with our Data Scientists throughout the entire machine learning lifecycle. While they focus on developing and validating machine learning models, your focus will be designing the cloud infrastructure, ML pipelines and operational tooling that enable these models to run reliably, scale efficiently and continuously improve in production.

In this role, you will:

• 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 the 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.

Skills & Requirements

• 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, with excellent written and spoken English; German is a plus.

At idealo you can expect

• You want to further your education? We take your personal development goals seriously and, in addition to our idealo Learning Hub, eLearning offerings (e.g., Udemy), coaching & mediation, we also offer you the opportunity to benefit individually from additional learning and development budget.

• And what about the office? Our office in the heart of Berlin offers free organic breakfast, excellent free lunch (vegan and vegetarian), as well as free coffee, lemonades and after-work beer, in addition to the "standard foosball". It also has a fabulous rooftop terrace with view of the whole of berlin where you can network with colleagues from our group of companies.

• In need of additional support in any areas of your life? We offer free counseling and support in all areas of life (professional, private, family, health, etc.) in cooperation with the pme-Familienservice.

• You want full flexibility on your way to work and beyond? No problem with a job bike or Deutschlandticket- and it's environmentally friendly, too!

• Want to keep yourself fit? We offer many different fitness and sports options, such as an Urban Sports or Gympass membership, to suit your personal needs.

• And what else is there? Of course, success must be celebrated! In addition to team events, you can also expect big company events and other moments of organized connection with others in the company and your team throughout the year!

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