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# Senior Infrastructure Engineer, AI & ML, Penguin Random House (Open to Remote)

- **Company:** Gruner + Jahr AG & Co KG
- **Location:** New York, Germany (Remote available)
- **Experience:** Expert
- **Salary:** €185,000 - €210,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Recommender Systems, Azure Machine Learning, Application Enhancement Tool, Cloud Platform System, Large Language Models, Agentic-AI, Machine Learning Operations
- **Published:** November 9, 2026
- **Apply:** https://jobsearch.createyourowncareer.com/talentcommunity/apply/1454857933/?locale=en_US

## About the Role

* 5+ years building and running production systems.

 * Track record of designing infrastructure components or tooling that other engineers or teams adopted.

 * Hands-on cloud experience (AWS preferred).

 * You can use AI agents to build and operate systems, and you can show work you shipped this way.

 * Strong communication skills and ability to work closely with data scientists and engineers.

 * Experience running infrastructure for ML or data-intensive workloads in production, such as model training, batch scoring or model serving.

Preferred Qualifications:

 * Experience defining SLOs or SLAs and managing cloud cost for ML production systems.

 * Experience with evaluation or error analysis of ML or LLM systems in production.

## Description

The Data Science team at Penguin Random House builds recommendation systems, forecasting models, and AI-powered tools that shape how readers discover books across our platforms. Our team of scientists and engineers develops and operates these systems end-to-end, from research through production., We are building a dedicated cloud environment on AWS, along with ML platforms that enable our scientists to deliver models to production quickly. We are hiring a Senior Infrastructure Engineer to build and maintain the foundational systems that support this work.

You will build on a mature MLOps foundation and work closely with AI to evolve and run our cloud platform.

Key Responsibilities:

 * Design and own core components of our AWS environment used across data science products. Set the standards for how people and AI agents change infrastructure: review, tests and guardrails.

 * Build self-service paths to production for scientists: CI/CD pipelines, promotion gates, and automated triggers, so scientists can ship models without hand-holding.

 * Help maintain the security, compliance, and reliability of cloud environments.

 * Shape the platform roadmap by identifying the infrastructure work that will most unblock our scientists, and keep stakeholders informed as it progresses., Responsible for processing the information provided in your application is the company specified in the job advertisement, with its registered office as indicated. The company processes your data for the purpose of establishing an employment relationship on the basis of Art. 6 (1) b GDPR / Section 26 (1) sentence 1 BDSG.

The retention period for your data is determined by the statutory time limits applicable in the respective country, beginning upon completion of the recruitment process. You can find these here.