Staff ML Engineer: Multimodal Content Intelligence

Deepstreamtech; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Deepstreamtech is looking for a Staff Machine Learning Engineer in Greater London to build and scale foundational machine learning systems that enhance content understanding across Spotify. The role involves collaborating with product, policy, and engineering teams to ensure high-quality user experiences and includes tasks such as developing models for classification and content enrichment. Ideal candidates will have experience in deploying ML systems and working with large datasets, with a focus on automation and quality.

Responsibilities

• Build and scale foundational ML systems for content understanding across Spotify.
• Work on systems that generate deep machine-readable understanding of content across modalities.
• Deliver safe, high-quality experiences for millions worldwide.
• Develop models for classification, tagging, and semantic understanding.
• Create high-quality content enrichment at scale.
• Design systems for content intelligence signals to be available to teams.
• Improve automation for content quality and metadata enrichment.
• Collaborate across teams to translate content intelligence into user impact.

Skills

Building and deploying machine learning systems

Familiarity with ML frameworks (PyTorch, TensorFlow)

Experience with large datasets

Understanding multimodal machine learning

Designing systems balancing automation and quality

Complex problem solving

Systems thinking

Clear communication

Job description

Deepstreamtech is looking for a Staff Machine Learning Engineer in Greater London to build and scale foundational machine learning systems that enhance content understanding across Spotify. The role involves collaborating with product, policy, and engineering teams to ensure high-quality user experiences and includes tasks such as developing models for classification and content enrichment. Ideal candidates will have experience in deploying ML systems and working with large datasets, with a focus on automation and quality.