Machine Learning Scientist – Remote

About the Company

Penguin Random House is a globally recognized leader in the publishing industry, known for its extensive portfolio of adult and children's books across diverse genres and subjects. As the largest trade publisher in North America, the United Kingdom, and beyond, Penguin Random House is committed to delivering high-quality, innovative, and engaging content. Our operations encompass every facet of publishing, including editorial, design, marketing, publicity, sales, production, and distribution, ensuring a seamless experience from manuscript to reader. With a vibrant international community comprising nearly 300 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, we foster a culture of excellence, creativity, and diversity.

About the Role

Penguin Random House is seeking a highly skilled and innovative Staff Machine Learning Scientist to join our Data Science team. This pivotal role involves leading the development and enhancement of personalization products, including recommender systems that power our websites, email campaigns, and online marketing initiatives. Personalization is a critical growth driver for book discovery and customer engagement, directly influencing how readers connect with our extensive catalog across digital platforms. The successful candidate will own the end-to-end lifecycle of personalization and recommender systems, from conceptualization and model development to deployment and ongoing monitoring. This position requires close collaboration with business stakeholders, platform engineers, and the broader personalization team to ensure scalable, maintainable, and high-performing solutions.

Penguin Random House boasts a mature machine learning infrastructure supported by robust data warehousing and DevOps capabilities. We are transitioning towards AI-accelerated development, utilizing modern agentic coding tools like Claude Code to streamline model building and maintenance processes. The ideal candidate will have a strong foundation in machine learning and a willingness to learn and adapt to new workflows, contributing to our goal of delivering measurable improvements in personalization quality and relevance.

Responsibilities

• Define and execute the technical roadmap for personalization and recommender systems aligned with business objectives.
• Lead research and development initiatives that inform product roadmaps and long-term project goals.
• Design, develop, and maintain scalable software systems used across multiple teams and products.
• Ensure personalization services meet SLAs, deliver accurate results, and adapt to evolving business needs.
• Establish and promote experimentation best practices, including A/B testing frameworks, offline evaluation methodologies, and metrics design.
• Lead team meetings, monitor project progress, and make critical technical decisions to unblock development efforts.
• Manage stakeholder expectations through data-driven narratives and effective communication with senior leadership.
• Implement new technologies and processes to improve organizational efficiency and business impact.
• Mentor junior and mid-level scientists, fostering a culture of high-quality code and best practices.
• Stay current with advances in recommender systems, large language models, and representation learning, integrating relevant innovations into production systems.

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.
• Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
• Experience with recommendation-specific tools like NVTabular, Merlin, Triton.
• Strong background in cloud-based ML infrastructure, including AWS, Kubernetes, and Databricks.
• Hands-on experience with containerization (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 strategies, and make durable architectural decisions.
• Excellent communication skills, capable of presenting complex technical concepts to diverse audiences.
• Demonstrated ability to leverage the latest AI tools and techniques to develop robust, innovative software solutions.

Benefits

• Competitive salary range of USD 210,000 - 250,000 per year.
• Eligibility for annual profit sharing or bonuses based on company performance.
• Comprehensive health benefits including medical, dental, and vision insurance.
• Flexible Spending Accounts for health and dependent care.
• Health Savings Account (HSA) and pre-tax/Roth 401(k) retirement plans.
• Short-term and long-term disability insurance, life and AD&D coverage.
• Commuter benefits and support programs.
• Student loan repayment assistance and educational support.
• Generous paid time off policies.