Sr. ML Ops Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Hybrid From the posting source checked Jun 20, 2026

In-office days

2 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Series A From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Sr. ML Ops Engineer US Remote | Hybrid | Mountain View, CA | Remote ABOUT CORVUS Every physical good spends time in a warehouse, and every warehouse tracks their inventory. Today, nearly 100% of warehouses track their inventory manually using barcode scanners and climbing forklifts. We're Corvus Robotics https://www.corvus-robotics.com/. Our fully autonomous Corvus One™ https://blog.corvus-robotics.com/corvus-one-launch-and-series-a-funding drones use computer vision & robotics to automatically track inventory, improving worker safety and increasing labor efficiency. We believe that data-driven, safe inventory management will optimize the global physical economy and improve economic prosperity for humanity. ABOUT THE ROLE With a growing fleet of autonomous drones and an expanding customer base, we're now ready to multiply ML iteration speed and unblock more advanced ML product delivery. We're hiring a systems-oriented Senior Software Engineer to build the data infrastructure, training pipelines, and internal tooling that our ML team needs to move faster. Specifically in this role you will: - Build and maintain the data pipeline infrastructure that consolidates internal infra, labeling tools, S3, and other data sources into a unified, queryable system - Build tooling for dataset selection and curation that can programmatically target specific data (by environment, object type, etc.) - Own ML data infra from robot to training run, accessible to the ML team without backend engineering help - Build model evaluation and regression testing infrastructure -- real metrics, not vibes or "someone complained in prod" - Automate the model retuning loop for standard tasks so ML engineers can be mostly hands-off on routine

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