Machine Learning Scientist

About the Company

Penguin Random House is the leading adult and children's publishing house operating across North America, the United Kingdom, and numerous other regions worldwide. Renowned for publishing high-quality books across every genre and subject for all ages, the company is committed to excellence in execution, innovation, and quality throughout every stage of the publishing process, including editorial, design, marketing, publicity, sales, production, and distribution. With a vibrant and diverse international community comprising nearly 300 publishing brands and imprints such as Ballantine Bantam Dell, Berkley, Clarkson Potter, Crown, DK, Doubleday, Dutton, Grosset & Dunlap, Little Golden Books, Knopf, Modern Library, Pantheon, Penguin Books, Penguin Press, Penguin Random House Audio, Penguin Young Readers, Portfolio, Puffin, Putnam, Riverhead, Ten Speed Press, Viking, and Vintage, the organization continuously strives to bring compelling stories to a global audience.

About the Role

Penguin Random House, as the largest trade publishing company globally, is seeking a highly skilled Staff Machine Learning Scientist to join its Data Science team. This role is pivotal in leading the development and enhancement of personalization products, including recommender systems deployed across websites, email campaigns, and online marketing channels. Personalization serves as a core growth lever for book discovery and customer engagement, directly influencing how readers find and connect with books across digital platforms. The successful candidate will own the end-to-end lifecycle of personalization and recommender system projects—from model development and deployment to output monitoring—working closely with business stakeholders, platform engineers, and the broader personalization group. The role involves leveraging a mature machine learning infrastructure supported by robust data warehouses and DevOps teams. The organization is transitioning towards AI-accelerated development, utilizing modern agentic coding tools such as Claude Code to expedite system building and maintenance, while ensuring rigorous quality standards through testing, reproducibility, and measurable performance improvements. The ideal candidate will possess strong fundamentals, adaptability, and a willingness to learn new workflows to stay at the forefront of AI and ML advancements.

Qualifications

• PhD in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or a related quantitative field, OR Master’s degree with 8+ years of applied ML experience.
• Deep expertise in recommender systems, personalization, ranking/retrieval, or computational advertising, with a proven track record of deploying scalable systems.
• Expert proficiency in Python, with extensive experience using modern ML frameworks such as PyTorch or TensorFlow, and recommendation-specific tools like NVTabular, Merlin, or Triton.
• Strong experience with cloud-based ML infrastructure including AWS, Kubernetes, and Databricks, alongside containerization skills with Docker and low-latency model serving.
• Advanced SQL skills and experience designing large-scale data pipelines and feature stores.
• Ability to define technical roadmaps, influence cross-team architecture, and make durable architectural decisions.
• Excellent communication skills capable of conveying complex technical concepts to both technical and non-technical audiences.
• Willingness to utilize the latest AI tools and incorporate cutting-edge research into production systems.

Responsibilities

• Define and steer the technical roadmap for personalization and recommender systems, aligning priorities with business objectives and setting a clear short-term vision for the team.
• Lead research and development initiatives that influence long-term product strategies, ensuring models are robust, scalable, and long-lasting across multiple products and teams.
• Design and develop software solutions used by various teams, emphasizing maintainability, scalability, and adaptability to evolving business needs.
• Ensure personalization products meet service level agreements (SLAs), deliver accurate results consistently, and adapt to changing operational requirements.
• Establish and uphold best practices for experimentation, including A/B testing frameworks, offline evaluation methodologies, and metric design to measure success effectively.
• Lead team meetings, monitor project progress, and make critical technical decisions to unblock development efforts.
• Manage stakeholder expectations through data-driven narratives and maintain effective communication with senior leadership to align strategies and track progress.
• Implement new technologies and processes to enhance organizational efficiency and maximize business impact.
• Mentor senior and mid-level scientists, promote high standards for coding, documentation, and best practices within the team.
• Stay informed on the latest advancements in recommender systems, large language models (LLMs), and representation learning, integrating relevant innovations into production workflows.

Benefits

• Competitive salary range of USD 210,000 - 250,000 annually, with eligibility for profit sharing or bonuses based on company performance.
• Comprehensive benefits package including medical and prescription drug insurance, dental, and vision coverage.
• Health Care and Dependent Care Flexible Spending Accounts, Health Savings Account options.
• Pre-Tax and Roth 401(k) retirement plans.
• Disability insurance (short-term and long-term), life and AD&D insurance.
• Commuter benefits and programs supporting work-life balance.
• Student loan repayment assistance and educational support programs.
• Generous paid time off policies to promote work-life harmony.