Staff ML Scientist, Personalization & Recommendations

SiriusXM; Dublin; On-site; EUR 120,000 - 170,000; Full time

Job summary

SiriusXM is seeking a Staff Machine Learning Scientist, Recommendations, to lead development of advanced recommendation and personalization systems powering content discovery across a broad audio ecosystem. You will influence technical direction and mentor teams, delivering scalable models that improve engagement for music, podcasts, channels, and live content.

This role requires 6+ years of production ML experience with strong knowledge of ranking and personalization, and a track record of

Qualifications

• 6+ years of production ML experience with scalable systems.
• Strong background in recommendation, ranking and personalization.
• Experience deploying ML solutions from concept to production.
• Proven ability to lead technical initiatives across teams.
• Excellent communication for technical and non-technical audiences.
• Collaborates effectively with product, engineering, analytics and business teams.

Responsibilities

• Lead design, development, deployment and continuous improvement of ML systems for recommendations and personalization.
• Drive complex initiatives: personalized recommendations, content ranking, real-time discovery.
• Apply deep learning, transformers and modern ML techniques to solve problems.
• Own major recommendation initiatives from problem definition to production monitoring.
• Establish scalable evaluation and measurement for model performance and impact.
• Collaborate with Product, Engineering, Analytics and Content teams to deliver ML solutions.
• Mentor scientists and engineers on methodologies and experimentation.

Skills

Machine Learning

Recommendation Systems

Ranking Models

Personalization

Deep Learning

Transformer Architectures

Production ML

Experimentation

Cross-functional Collaboration

Leadership

Education

MS in Computer Science

PhD preferred

Job description

SiriusXM is seeking a Staff Machine Learning Scientist, Recommendations, to lead development of advanced recommendation and personalization systems powering content discovery across a broad audio ecosystem. You will influence technical direction and mentor teams, delivering scalable models that improve engagement for music, podcasts, channels, and live content.

This role requires 6+ years of production ML experience with strong knowledge of ranking and personalization, and a track record of