Lead-Scale ML Engineer for Safe Content & Policy

Creandum Advisor LLP; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Creandum Advisor LLP is looking for a Senior Staff Machine Learning Engineer to build and scale ML systems that ensure safety, policy enforcement, and compliance across Spotify’s content. This role involves defining machine learning strategies, developing automated decisioning systems, and collaborating across teams to maintain high standards of content quality.

The ideal candidate should have strong experience with production-grade ML systems and modern frameworks like PyTorch and TensorFlow. The position offers flexibility to work from home while requiring occasional in-person meetings.

Qualifications

• Strong experience building production-grade machine learning systems at scale.
• Experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.
• Understanding of systems where ML outputs influence real-world decisions.

Responsibilities

• Define & drive machine learning strategy for safety, policy enforcement, and compliance systems.
• Build and scale ML systems for detection, classification, and risk assessment across content.
• Develop automated decisioning systems that ensure consistent, reliable enforcement of policies.

Skills

Building production-grade machine learning systems

Experience with PyTorch

Experience with TensorFlow

System design balancing automation and safety

Job description

Creandum Advisor LLP is looking for a Senior Staff Machine Learning Engineer to build and scale ML systems that ensure safety, policy enforcement, and compliance across Spotify’s content. This role involves defining machine learning strategies, developing automated decisioning systems, and collaborating across teams to maintain high standards of content quality.

The ideal candidate should have strong experience with production-grade ML systems and modern frameworks like PyTorch and TensorFlow. The position offers flexibility to work from home while requiring occasional in-person meetings.