Research Scientist, Personalization & ML

Ernst & König GmbH; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Extensive learning opportunities

Flexible share incentives

Global parental leave

All The Feels employee assistance

Job summary

Spotify’s Personalization team is seeking a researcher to advance ML/AI for large-scale personalization. You will design experiments, develop models and evaluation frameworks, and contribute to publications and talks while collaborating with cross-functional partners to shape long-term product opportunities.

You will have a Master’s or PhD in ML/AI or equivalent experience, with proven publications and hands-on expertise in reinforcement learning and post-training methods for large models.

Qualifications

• PhD or Master’s in machine learning, AI or a related field, or equivalent research experience.
• Demonstrated expertise in ML/AI through peer-reviewed publications at major conferences.
• Experience with post-training methods and reinforcement learning for large models.

Responsibilities

• Conduct original research in ML/AI focusing on foundation models, generative AI and post-training methods.
• Develop novel methodologies, models and evaluation frameworks for personalization systems.
• Design and run rigorous experiments to validate research hypotheses.
• Collaborate with cross-functional teams to translate insights into product opportunities.

Skills

Machine learning

Reinforcement learning

Experiment design

Large-scale models

Research methods

Collaboration

Education

Master’s or PhD in ML/AI or related field

Job description

Spotify’s Personalization team is seeking a researcher to advance ML/AI for large-scale personalization. You will design experiments, develop models and evaluation frameworks, and contribute to publications and talks while collaborating with cross-functional partners to shape long-term product opportunities.

You will have a Master’s or PhD in ML/AI or equivalent experience, with proven publications and hands-on expertise in reinforcement learning and post-training methods for large models.