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Staff Machine Learning Scientist – Personalization
Bertelsmann SE & Co. KGaAStaff Machine Learning Scientist leading the development of personalization products for Penguin Random House. Focus on recommender systems and customer engagement across digital platforms.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in defining technical roadmaps for personalization and recommender systems, with a strong focus on delivering scalable solutions and managing cross-team collaborations. Proficient in mentoring and fostering a high-performance team culture while ensuring adherence to best practices in experimentation and model deployment.
Highest-signal resume keywords
Recommender Systems ExpertiseExpert-Level PythonCloud-Based ML InfrastructureTechnical Roadmap DefinitionAdvanced SQL Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningPersonalizationRanking/RetrievalComputational AdvertisingDeep Learning FrameworksData Pipeline ArchitectureFeature Store ManagementA/B Testing FrameworksMetrics DesignModel Serving
Soft Skills
Excellent CommunicationTeam LeadershipStakeholder ManagementMentoring
Tools & Technologies
PyTorchTensorFlowAWSKubernetesDatabricksDockerNVTabularMerlinTriton
Certifications & Qualifications
PhD in Computer ScienceMaster's in Related Field
Industry Keywords
Personalization ProductsMulti-Service SystemsExperimentation Best PracticesData-Driven NarrativesLong-Term Maintainability
Tech Stack
Tools & technologiesAWSCloudDockerKubernetesPythonPyTorchSQLTensorflow
About the role
Key responsibilities & impact- 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. Models are used over the long term by multiple products and teams.
- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- 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