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ML Engineer

Monarch· R&D
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Emeryville, CaliforniaFull-timePosted 1mo ago

About the role

Build reliable systems that carry data from assay recording to reproducible model, evaluated prediction, and usable recommendations for the next experiment.

Responsibilities

  • Own pipelines for ingesting, validating, versioning, and joining assay videos, metadata, compound records, model features, and experimental outcomes
  • Build reproducible training and evaluation infrastructure with clear data lineage, model versioning, automated tests, and auditable outputs
  • Turn research prototypes into dependable batch and online systems that can rank compounds and surface recommendations through our tools
  • Monitor data quality, distribution shift, calibration, latency, cost, and failures as the number of labs and assays grows
  • Design interfaces between computer vision, molecular models, active-learning systems, and the lab workflow
  • Improve developer and researcher velocity without weakening scientific reproducibility or access controls

Qualifications

  • Strong production software engineering experience in Python and modern machine-learning or data systems
  • Experience deploying and operating model-training, feature, evaluation, or inference pipelines in a cloud environment
  • Fluency with testing, observability, data validation, version control, and reproducible computational workflows
  • Ability to work with large video datasets and structured scientific data
  • Ability to collaborate closely with researchers while making sound engineering tradeoffs

Skills

Required:PythonModel pipelines

Benefits

  • Compensation includes equity
Last updated Oct 7, 2026. Interested? Apply on the company site.

About Monarch

Monarch is developing a scalable, precision-based approach to protect crops from insects.

Company profileWebsite

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