Company
Tech / AI / Software
StaffMachineLearningEngineer-ContentIntelligence
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Machine Learning Engineer - Content Intelligence. Skills: machine learning systems, content intelligence, multimodal machine learning. Build and scale machine learning systems that generate deep understanding of content across modalities. Develop models for classification, tagging, semantic understanding, and content enrichment”
What You'll Achieve.
generate deep understanding of content across modalities; Create high quality content enrichment at scale; make content intelligence signals available to downstream teams and products; Improve automation for content quality, safety, and metadata enrichment at scale; translate content intelligence into user impact; launch new types of content signals; improve system reliability, scalability, and performance across large datasets
Industry & Context.
think in systems; understand how models connect to product outcomes; working on complex problems with evolving requirements
What They're Looking For.
Must Have
experience building and deploying machine learning systems in production, working with large datasets, data quality and evaluation, design systems that balance automation with quality and user experience, working on complex problems with evolving requirements, think in systems, understand how models connect to product outcomes
Nice to Have
interested in or have worked with multimodal machine learning
What You'll Do.
Build and scale machine learning systems that generate deep understanding of content across modalities
Develop models for classification
semantic understanding
and content enrichment
Create high quality content enrichment at scale using LLMs and agentic systems
Design systems that make content intelligence signals available to downstream teams and products
Improve automation for content quality
and metadata enrichment at scale
Contribute to evaluation frameworks
and annotation systems
Support rapid experimentation to prototype and launch new types of content signals
Help improve system reliability
and performance across large datasets
How You'll Work.
Team & Collaboration
Collaborate with product, policy, and engineering teams to translate content intelligence into user impact; work well across technical and non-technical teams
Communication Scope
communicate clearly
Full Job Description
## What You Will Do Build and scale machine learning systems that generate deep understanding of content across modalities Develop models for classification, tagging, semantic understanding, and content enrichment Create high quality content enrichment at scale using LLMs and agentic systems. Design systems that make content intelligence signals available to downstream teams and products Improve automation for content quality, safety, and metadata enrichment at scale Collaborate with product, policy, and engineering teams to translate content intelligence into user impact Contribute to evaluation frameworks, data pipelines, and annotation systems Support rapid experimentation to prototype and launch new types of content signals Help improve system reliability, scalability, and performance across large datasets ## Who You Are You have experience building and deploying machine learning systems in production You are comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar You have experience working with large datasets and care about data quality and evaluation You are interested in or have worked with multimodal machine learning You understand how to design systems that balance automation with quality and user experience You are comfortable working on complex problems with evolving requirements You think in systems and understand how models connect to product outcomes You communicate clearly and work well across technical and non-technical teams ## Where You Will Be This role is based in London or Stockholm We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
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