Senior Staff Machine Learning Scientist, Recommendations
Skills
About the role
Dublin, Ireland
Regular Employee Full-Time
R-2026-03-64
Hybrid
Who We Are:
SiriusXM and its brands (Pandora, SiriusXM Media, AdsWizz, Simplecast, and SiriusXM Connect) are leading a new era of audio entertainment and services by delivering the most compelling subscription and ad-supported audio entertainment experience for listeners - in the car, at home, and anywhere on the go with connected devices. Our vision is to shape the future of audio, where everyone can be effortlessly connected to the voices, stories and music they love wherever they are.
This is the place where a diverse group of emerging talent and legends alike come to share authentic and purposeful songs, stories, sounds and insights through some of the best programming and technology in the world. Our critically-acclaimed, industry-leading audio entertainment encompasses music, sports, comedy, news, talk, live events, and podcasting. No matter their individual role, each of our employees plays a vital part in bringing SiriusXM’s vision to life every day.
SiriusXM is the leading audio entertainment company in North America, and the premier programmer and platform for subscription and digital advertising-supported audio products. SiriusXM’s platforms collectively reach approximately 150 million listeners, the largest digital audio audience across paid and free tiers in North America, and deliver music, sports, talk, news, comedy, entertainment and podcasts.
Pandora, a subsidiary of SiriusXM, is the largest ad-supported audio entertainment streaming service in the U.S. SiriusXM's subsidiaries Simplecast and AdsWizz make it a leader in podcast hosting, production, distribution, analytics and monetization. The Company’s advertising sales organization, which operates as SiriusXM Media, leverages its scale, cross-platform sales organization and ad tech capabilities to deliver results for audio creators and advertisers. SiriusXM, through SiriusXM Canada Holdings, Inc., also offers satellite radio and audio entertainment in Canada. In addition to its audio entertainment businesses, SiriusXM offers connected vehicle services to automakers.
How you’ll make an impact:
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.
What you’ll do:
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.
What you’ll need:
Education: 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
The requirements and duties described above may be modified or waived by the Company in its sole discretion without notice.
R-2026-03-64
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