Remote Research Scientist, Personalization & ML

Promptcube3; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Flexible work arrangements

Job summary

Spotify is seeking a Research Scientist in Personalization to advance machine learning for personalized recommendations. Based in London with flexibility for remote work, you will conduct original research on large-scale models, reinforcement learning, and post-training methods, aiming to drive long-term product opportunities.

You’ll publish findings, present at conferences, and mentor colleagues while collaborating with cross-functional teams to translate insights into scalable, impactful

Qualifications

• Master's or PhD in machine learning, AI, or a related field.
• Peer-reviewed publications in top conferences (NeurIPS, ICML, ICLR, KDD, RecSys).
• Hands-on experience in post-training and reinforcement learning for large models.
• Experience designing experiments with real-world datasets to validate ideas.

Responsibilities

• Conduct original ML/AI research focused on foundation models, generative AI, and RL.
• Develop novel methodologies, models, and evaluation frameworks.
• Design and run rigorous experiments to test hypotheses and compare approaches.
• Collaborate with cross-functional teams to translate insights into product opportunities.
• Mentor others and contribute to a collaborative research culture.

Skills

Machine learning

Reinforcement learning

Experiment design

Large-scale ML

Research collaboration

Education

Master's degree in ML/AI

PhD in ML/AI or related field

Tools

PyTorch

TensorFlow

Distributed training

Job description

Spotify is seeking a Research Scientist in Personalization to advance machine learning for personalized recommendations. Based in London with flexibility for remote work, you will conduct original research on large-scale models, reinforcement learning, and post-training methods, aiming to drive long-term product opportunities.

You’ll publish findings, present at conferences, and mentor colleagues while collaborating with cross-functional teams to translate insights into scalable, impactful