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Amsterdam
7 Apr 2026
Lead ML Engineer (recommendation systems) logo

Lead ML Engineer (recommendation systems)

Swap

Amsterdam
7 Apr 2026
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Lead ML Engineer (recommendation systems)

Lead ML Engineer (recommendation systems) role at Swap, an AI-native commerce platform. Requires 5+ years experience building production recommendation systems, expertise in Python, ML frameworks, and LLMs. Responsibilities include end-to-end ML lifecycle for style-aware recommendations and personalization.

On-siteFull-timeLeadVersion ControlCollaborative Filtering

Lead ML Engineer (recommendation systems)

Lead ML Engineer (recommendation systems) role at Swap, an AI-native commerce platform. Requires 5+ years experience building production recommendation systems, expertise in Python, ML frameworks, and LLMs. Responsibilities include end-to-end ML lifecycle for style-aware recommendations and personalization.

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On-siteFull-timeLeadVersion Control

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site

Experience Required

5 years

Employment Type

Full-time

Experience Level

Senior/Lead ML Engineer

Core Qualifications

Technical (Must-have)
version controlcollaborative filteringCI/CDPyTorchgraph-based approachesPythonLLMscontent-based methodsTensorFlowembedding modelsfeature enrichmentsequence models
Soft Skills
claritycreativityshared ownership

Preferred Qualifications

Technical (Nice-to-have)
visual embeddingsmultimodal modelstaste/preference modelling

Key Responsibilities

  • •Own the end-to-end ML lifecycle for recommendation and personalisation systems
  • •Design, build, and productionise models for style-aware recommendations
  • •Develop approaches that combine conversational preference extraction with traditional behavioural signals and LLM-based world knowledge
  • •Build and optimise the feature pipelines and serving infrastructure that power recommendations at scale
  • •Define and champion best practices for offline and online evaluation of recommendation quality
  • •Collaborate closely with product, AI engineering, and design to shape how recommendations surface across the AI Storefront
  • •Explore and integrate signals from social media content and visual style to enrich user taste profiles
  • •Act as a senior technical reference point for recommendation and personalisation engineering at Swap
Lead ML Engineerrecommendation systemsAI-native platformcommercePythonLLMsfashionstyle-awarepersonalizationproduction ML
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