Senior Infrastructure Engineer, AI & ML, Penguin Random House (Open to Remote)
(Calculated after EPF (12%), Gratuity (4.81%), Professional Tax & New Tax Regime FY 2025-26 deductions)
- Target Role:Senior Infrastructure Engineer, AI & ML, Penguin Random House (Open to Remote)
- Employer:Bertelsmann-Jobs
- Work Mode:REMOTE
- Location:Remote (United States)
- Compensation:USD 185,000 - 210,000 / annual
- Experience:2+ Years
- Recruiter SLA:7-Day Truth Teller Guarantee
- Candidate Fee:₹0 (Zero Placement Fee Guarantee)
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About the Role
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. 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
Requirements & Qualifications
- Strong problem solving foundations, knowledge of modern engineering practices, and interest in technology systems.
Perks & Benefits
- Official mentor support
- verified hiring timeline
- and career progression.
The employer seeks candidates proficient in the following core technologies:
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The verified package for this role is USD 185,000 - 210,000 / annual (REMOTE). RoleNest enforces transparent compensation benchmarking to eliminate guessing before candidates invest time in assessments.
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Engineers with 2+ years of experience proficient in AWS, DevOps are encouraged to apply.
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