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Penguin Random House

Staff Machine Learning Scientist – Personalization

RemoteUnited States only
Published
Role
AI / ML
Experience
Staff
Employment
Full-time
Company size
Enterprise
$210k–$250k/yr
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Staff-level ML scientist for personalization and recommender systems, owning models end-to-end from development to deployment and monitoring. Needs PhD or Master’s with 8+ years applied ML, expert Python, modern ML frameworks, SQL, cloud ML infrastructure, and large-scale data pipelines.

Core skills

PythonPyTorch/TensorFlowRecommender Systems

Required skills

NVTabularMerlinTritonAWSKubernetesDatabricksDockerSQL

Optional skills

Claude CodeA/B testingCausal inferenceLLM-based recommendationMLOpsModel monitoringFeature storesCI/CD for ML

What you'll do

  • Define and drive the technical roadmap for personalization and recommender systems, prioritizing roadmap items to meet business goals and defining short-term vision for the team.
  • Propose and deliver R&D that directly shapes roadmaps, multiple projects, and long-term deliverables.
  • Design and lead the development of software used by multiple teams, ensuring long-term maintainability, scalability, and adaptability.
  • Ensure complex, multi-service personalization products meet SLAs and provide correct results over time.
  • Adapt systems to changing business needs and resolve multi-product, multi-team service incidents.
  • Establish and enforce experimentation best practices, including A/B testing frameworks, offline evaluation methodology, and metrics design across personalization surfaces.
  • Lead team meetings, ensure the team's progress on the roadmap, and make technical decisions that unblock projects.
  • Manage stakeholders' expectations with data-driven narratives and communicate effectively with senior leadership to align on strategy and track progress.
  • Drive organizational efficiency and business impact by implementing new technologies and processes.
  • Foster a collaborative and high-performance team culture.
  • Mentor senior and mid-level scientists, setting high code quality standards and best practices for the team.
  • Stay current with advances in recommender systems, LLMs for personalization, and representation learning, bringing relevant advances into production when they deliver measurable improvement.

What they require

  • PhD in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or a related quantitative field, OR Master's with 8+ years of applied ML experience.
  • Deep expertise in recommender systems, personalization, ranking/retrieval, or computational advertising, with a track record of shipping systems that operate at scale.
  • Expert-level Python and deep proficiency with modern ML frameworks (PyTorch or TensorFlow) and recommendation-specific tooling (e.g., NVTabular, Merlin, Triton).
  • Strong experience with cloud-based ML infrastructure (AWS, Kubernetes, Databricks), containerization (Docker), and model serving at low latency.
  • Advanced SQL skills and experience architecting large-scale data pipelines and feature stores.
  • Demonstrated ability to define technical roadmaps, influence direction across teams, and make architectural decisions that hold up over time.
  • Excellent communication skills with the ability to present complex technical work to executive and non-technical audiences.
  • Be cutting edge.
  • Use the latest AI tools to develop well-designed and robust software.
  • Preferred: Experience building and scaling real-time recommendation services handling millions of requests.
  • Preferred: Expertise in A/B testing methodology, causal inference, or experimentation platforms.
  • Preferred: Familiarity with LLM-based approaches to recommendation and content understanding.
  • Preferred: Experience with MLOps practices: model monitoring, feature stores, CI/CD for ML, and automated retraining pipelines.
  • Preferred: Prior experience technically leading a team of ML practitioners and setting standards adopted by others.

Benefits

  • All positions are currently eligible for an annual profit award or bonus, subject to company results.
  • Medical/Prescription drug insurance
  • Dental
  • Vision
  • 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

multinational conglomerate publishing company

PublishingEnterpriseglobal.penguinrandomhouse.com/
$210k–$250k/yr