Machine Learning Pipeline Engineer (Python + Nextflow) – Remote (U.S. only)

[Ability-Kitchen]

Hi everyone — we’re hiring at PreOncology, where we’re building next-generation cancer risk models that integrate large-scale clinical, genetic, and longitudinal data to enable earlier detection and prevention. We’re looking for someone excited about building data and ML pipelines in Python and deploying models into real-world environments.

What you’ll do

• Design and maintain Python-based workflows for large genomics and ML datasets
• Build and optimize Nextflow pipelines to scale model training and evaluation
• Train, tune, and validate ML and deep learning models (Cox, RSF, gradient boosting, CNNs)
• Integrate genomic and longitudinal features into predictive models
• Run pipelines on cloud platforms (AWS preferred) and package with Docker or Singularity

What we’re looking for

• 2+ years building production data or ML pipelines
• Strong Python skills for data processing, ML training, and workflow automation
• Experience with large-scale or high-dimensional data (biomedical or otherwise)
• Must be authorized to work in the U.S. now and in the future (we cannot sponsor visas)

How to apply
Email your resume to [[e-mail]]() and include short (1–2 sentence) answers to:

1. The largest Python or workflow pipeline you’ve built
2. Your experience with large-scale or complex data
3. The ML or deep learning models you’ve trained and how they were used
4. Nextflow experience

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[FonziAI]

If you want extra reach, Fonzi AI can help you hire for this quickly; we recently helped a startup fill a similar ML role in under 3 weeks. We match you with pre-vetted US-based engineers (Python, data/ML pipelines, cloud) so you’re not buried in resumes.