Senior Infrastructure Engineer, AI & ML

Bertelsmann SE & Co. KGaA

. Build and maintain foundational systems supporting Penguin Random House’s data science work .

Posted 11/5/2026full-timeRemote • New York • United StatesSenior💰 $185,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining cloud infrastructure, particularly within AWS, while ensuring security, compliance, and reliability for data science applications. Proven ability to collaborate with data scientists and engineers to enhance production systems and streamline workflows using AI agents.

Highest-signal resume keywords

AWS Cloud ExperienceProduction Systems ManagementInfrastructure DesignCI/CD Pipeline DevelopmentMachine Learning Operations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Production SystemsInfrastructure Components DesignCloud SecurityCI/CD PipelinesMachine Learning WorkloadsSLOs ManagementSLAs ManagementError AnalysisAI Agents UtilizationData Science Tools

Soft Skills

Strong CommunicationCollaboration

Industry Keywords

Data ScienceCloud EnvironmentsInfrastructure StandardsModel TrainingBatch ScoringModel ServingCloud Cost ManagementProduction SystemsStakeholder CommunicationPlatform Roadmap

Tech Stack

Tools & technologies

AWSCloud

About the role

Key responsibilities & impact

Build and maintain foundational systems supporting Penguin Random House’s data science work
Design and own core components of the AWS environment used across data science products
Set standards for how people and AI agents change infrastructure, including reviews, tests and guardrails
Build self-service paths to production for scientists, including CI/CD pipelines, promotion gates and automated triggers
Help maintain the security, compliance and reliability of cloud environments
Shape the platform roadmap by identifying infrastructure work that will unblock scientists
Keep stakeholders informed as platform work progresses
Work closely with AI to evolve and run the cloud platform

Requirements

What you’ll need

5+ years building and running production systems
Track record of designing infrastructure components or tooling adopted by other engineers or teams
Hands-on cloud experience (AWS preferred)
Ability to use AI agents to build and operate systems, with demonstrable shipped work
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
Experience defining SLOs or SLAs and managing cloud cost for ML production systems (preferred)
Experience with evaluation or error analysis of ML or LLM systems in production (preferred)
Resume and cover letter required for consideration

Benefits

Comp & perks

Annual profit award or bonus, subject to Company results
Medical/Prescription drug insurance
Dental insurance
Vision insurance
Health Care/Dependent Care Flexible Spending Account
Health Savings Account
Pre-Tax and Roth 401(k)
Short- and Long-Term Disability Insurance
Life/AD&D Insurance
Commuter Benefits
Student Loan Repayment Program
Educational Assistance
Generous paid time off