Senior Staff Machine Learning Scientist, Recommendations

About the Company

SiriusXM and its family of brands, including Pandora, SiriusXM Media, AdsWizz, Simplecast, and SiriusXM Connect, are helping define a new era of audio entertainment and services. The company delivers subscription-based and ad-supported audio experiences wherever listeners are: in the car, at home, or on the move through connected devices.

Its mission is to create a future of audio where people can instantly connect with the voices, stories, and music they enjoy. Across music, sports, comedy, news, talk, live events, and podcasts, SiriusXM combines strong content and advanced technology to serve listeners at scale.

SiriusXM is the leading audio entertainment company in North America and a major platform for subscription and digital advertising-supported audio products. Its services reach about 150 million listeners across paid and free tiers in North America. Pandora is its largest ad-supported streaming service in the U.S., while Simplecast and AdsWizz support podcast hosting, production, distribution, analytics, monetization, and advertising technology. The company also provides connected vehicle services and operates in Canada through SiriusXM Canada Holdings, Inc.

Role Overview

As a Senior Staff Machine Learning Scientist focused on recommendations, you will help shape how millions of listeners discover what to play next. The role sits at the intersection of machine learning, large-scale ranking systems, and product impact, with direct influence on personalized experiences across discover surfaces such as home pages and other recommendation touchpoints.

You will contribute to the next generation of personalization models across many content types, including channels, radio stations, shows, podcasts, live sports, news, and talk programming. The position calls for strong technical leadership in recommender systems, real-time systems, and ML-driven product development.

Responsibilities

• Develop and refine recommendation models using classical approaches, deep learning methods, transformer architectures, and other AI-based techniques for multiple audio recommendation use cases.
• Create new approaches for cross-domain recommendations, live content discovery, multi-stakeholder ranking, and more explainable and interactive recommendation experiences.
• Track model performance through offline evaluation and A/B experiments, then iterate to improve both business outcomes and listener experience.
• Set up and grow strong ML development, deployment, and evaluation practices across the recommendation stack.
• Partner closely with product managers, backend engineers, data engineers, and machine learning engineers to plan and deliver roadmaps for personalization products.
• Keep pace with modern ML and AI advances and apply them to difficult ranking and recommendation problems.
• Help define the technical vision and strategy for recommendation and personalization systems across the organization.
• Support team growth by mentoring junior colleagues, reviewing code carefully, and encouraging knowledge sharing and continuous learning.

Requirements

• Master’s degree in a quantitative discipline is required; a Ph.D. is preferred.
• At least 7 years of production experience building recommender systems and scaling machine learning pipelines and models.
• Strong programming experience in Python, Java, Scala, or similar languages.
• Practical knowledge of production ML workflows such as model versioning, tracking, deployment, monitoring, and feature store-based serving.
• Deep familiarity with modern recommendation methods, including transformers, deep-learning-based ranking models, and LLM or agent-based recommendation approaches.
• Excellent written and verbal communication skills, with the ability to explain technical solutions to scientists, engineers, and product stakeholders.
• Self-driven, growth-minded, and comfortable working on complex and challenging problems.
• Ability to work with cross-functional teams in a fast-moving product and engineering environment.

Additional Information

SiriusXM maintains a workplace built on respect, professionalism, and collaboration. The company is an equal opportunity employer and does not discriminate on the basis of race, creed, color, religion, national origin, ancestry, citizenship status, age, disability, sex, gender identity, marital status, family status, veteran status, sexual orientation, or any other legally protected characteristic.

The company reserves the right to change or waive the duties and requirements described in this posting at its sole discretion and without prior notice.

Reference: R-2026-03-64