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ML Data Engineer

United Kingdom, London · Job Posted February 20, 2026
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Job Description

At Recraft, we’re building the next generation of generative models across images and text. We’re looking for an ML Data Engineer to scale our data pipelines for unstructured data (primarily images) and keep our training flows fast, reliable, and repeatable. You’ll design and operate high-throughput ingestion and preprocessing on Kubernetes, evolve our internal data-pipeline framework, and work hand-in-hand with ML engineers to ship datasets that move model quality forward.

Job Responsibility

  • Develop and maintain data-ingestion pipelines to source and prepare large-scale image (and occasional text/HTML) datasets from open, publicly accessible, and permitted sources
  • Own the end-to-end flow: raw data → quality/beauty/relevance filtering → dedup/validation → ready-to-train artifacts
  • Operate and improve our Kubernetes-based data-pipeline framework (distributed jobs, retries, monitoring, automation)
  • Work with S3-style object storage: efficient layouts, lifecycle, throughput, and cost awareness
  • Add tooling around pipelines (progress/health visualization, metrics, alerts) for observability and faster iteration
  • Collaborate closely with ML engineers to align datasets with training needs and accelerate experimentation

Requirements

  • Strong Python fundamentals
  • you write clean, maintainable, production-ready code
  • Solid hands-on Kubernetes experience (containers, jobs, batch/distributed processing)
  • Proven track record with unstructured data, especially images (loading, filtering, transforming at scale)
  • Experience developing data-ingestion or parsing tools for publicly accessible sources, including handling real-world reliability and failure cases gracefully
  • Comfort with S3/object storage and moving lots of data efficiently and safely
  • Pragmatic, detail-oriented, ownership mindset
  • you enjoy making systems reliable and fast

Nice to have

  • Familiarity with ML workflows (PyTorch) and downstream training considerations
  • Experience with image quality scoring, captioning, or image-to-text pipelines
  • DAG/workflow visualizations or pipeline UX tooling
  • DevOps fluency: Docker, CI/CD, infra automation

What we offer

  • Competitive salary and equity
  • We’re able to offer Skilled Worker visa sponsorship in the UK for qualified candidates
  • Real impact on model quality: your pipelines directly power training runs and product improvements
  • Ownership with support: autonomy to design and improve systems, alongside experienced ML peers
  • Modern stack: Python, Kubernetes, S3, internal pipeline framework built for scale
  • Growth: a fast-moving environment where shipping well-engineered systems is the norm

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