# ML Engineer at Monarchcrops

> Onsite · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Amonarchcrops%3Adee35c8e-d6f4-4cc2-b019-0f73ec2eba23 (read 2026-11-10).

## Facts (observed)

- Company: [Monarchcrops](https://alderhq.app/companies/monarchcrops)
- Location text: Emeryville, California
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: Emeryville, California")
- Posted: 2026-09-05 (66 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/monarchcrops/dee35c8e-d6f4-4cc2-b019-0f73ec2eba23
- Skills listed (inferred): Python, GCP, PyTorch, TensorFlow

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (SF Bay Area, n 461): p25 $200k, median $250k, p75 $300k

## Description (the employer's text)

We offer opportunities to do your life’s work while helping solve one of the most important technical and moral challenges of our time.

Full-time, in-office in Emeryville, California. Compensation includes equity.

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

Key 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

Desired Attributes

• Experience with PyTorch, JAX, or TensorFlow and workflow-orchestration tools

• Experience on Google Cloud or with large-scale object-storage pipelines

• Familiarity with computer vision, molecular machine learning, active learning, or scientific data platforms

• Instinct for simple systems, explicit failure modes, and measurable reliability

To learn more, visit monarchlabs.org

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Amonarchcrops%3Adee35c8e-d6f4-4cc2-b019-0f73ec2eba23 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.