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Senior Staff Machine Learning Scientist, Recommendations

Ireland, Dublin · Job Posted June 30, 2026
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Job Description

At SiriusXM and Pandora, recommendations sit at the core of the user experience. As a Senior Staff Machine Learning Scientist, Recommendations, you will shape how tens of millions of listeners discover what to listen to next and push the frontier of large-scale recommender systems. Your work will directly define and advance the next generation of ranking and personalization models across our diverse audio content (channels, radio stations, shows, podcasts, live sports, news, talk, etc.) in our Discover home page experiences. You will operate at the intersection of deep learning, real-time systems, and measurable product impact.

Job Responsibility

  • Design, build, and improve traditional, deep-learning, transformer-based, and AI-based personalised recommendation models for various audio-content recommendation tasks
  • Drive the development of novel methods to enable cross-domain recommendations, live on-the-air content recommendations, multi-stakeholder recommendations, and improved recommendation explainability and interactivity
  • Continuously monitor, evaluate, optimise, and improve model performance, ensuring alignment with business goals and high-quality user experiences via offline metrics and A/B testing
  • Establish and scale best practices for ML development, deployment, and evaluation
  • Lead cross-functional efforts with product, backend engineers, data engineers, and machine learning engineers to define and drive roadmaps across multiple recommendation and personalisation surfaces
  • Stay up-to-date with the latest techniques in machine learning and apply these advancements to solve complex problems in recommendations and ranking, helping set the technical direction and vision for personalisation in a rapidly evolving ML and AI landscape
  • Own and influence the technical strategy for recommendation and personalisation systems across the organisation
  • Elevate the team’s capabilities by mentoring junior members, conducting thorough code reviews, and fostering an environment of shared knowledge and continuous learning

Requirements

  • M.S. in a quantitative field required
  • Ph.D. preferred
  • 7+ years production experience implementing recommender systems, machine learning pipelines, models at scale in Python, Java, Scala, or similar languages
  • Production ML: Knowledge of production ML best practices such as model versioning, tracking, deployment, monitoring
  • serving concepts such as feature stores, etc.
  • ML Concepts: Expertise with modern ML approaches for recommendations such as transformers, other deep-learning based recommender/ranking approaches, and LLM/agentic recommendation approaches
  • Soft Skills: Excellent written and verbal communication skills, with the ability to effectively advocate technical solutions to scientists, engineers, and product audiences
  • Mindset: Self-motivated, growth-oriented, and driven to pursue solutions to challenging problems

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