Corvus Robotics

Technology

Sr.MLOpsEngineer

$150–220k ~AI est. United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Sr. ML Ops Engineer at Corvus Robotics. Skills: ML Ops, Data Engineering, Robotics, Computer Vision. Build data pipeline infrastructure. Consolidate data sources”

Industry & Context.

Technology
Eligibility Requirements

Periodic trips to HQ

What They're Looking For.

Must Have

2-3 years shipping production ML infrastructure, Experience building distributed data pipelines, Demonstrated understanding of data flow, Experience building systems from scratch, Ability to thrive in startup environment

Nice to Have

Experience setting up annotation tooling, Background in robotics autonomy, Background in computer vision, Experience integrating with Kubeflow, Experience integrating with SLURM

What You'll Do.

Build data pipeline infrastructure

Consolidate data sources

Build tooling for dataset selection

Build tooling for dataset curation

Target specific data programmatically

Build model evaluation infrastructure

Build regression testing infrastructure

Automate model retuning loop

Full Job Description

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 updates This is a hybrid or remote role with periodic trips to HQ in Mountain View, CA. MUST HAVES - 2-3 years shipping real production ML infrastructure for big datasets, not just scripts - Experience building distributed data pipelines that consolidate multiple sources - Demonstrated understanding of data flow from raw collec

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