Corvus Robotics

Sr. ML Ops Engineer

Corvus Robotics
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5 months ago
Remote, United States or Mountain View, CA, USASenior
H1B sponsor

Responsibilities

  • Build and maintain data pipeline infrastructure that unifies internal infrastructure, labeling tools, S3, and other data sources into a queryable system.
  • Build programmatic tooling for dataset selection and curation by environment, object type, and other criteria.
  • Own ML data infrastructure from robot data collection through training runs for direct use by the ML team.
  • Build model evaluation and regression testing infrastructure with measurable metrics.
  • Automate routine model retuning workflows so ML engineers can operate them with minimal manual involvement.

Requirements

  • 2–3 years of experience shipping production ML infrastructure for large datasets.
  • Experience building distributed data pipelines that consolidate multiple data sources.
  • Understanding of the data flow from raw data collection through labeled training sets to trained models.
  • Experience building systems from scratch or making substantial contributions to infrastructure in a small team without an established playbook.
  • Ability to work effectively in a high-ambiguity startup environment.
  • Experience setting up annotation tooling and workflows is preferred.
  • Background in robotics autonomy and computer vision is preferred.
  • Experience integrating scalable training workflows with Kubeflow, SLURM, or similar tools is preferred.

Benefits

  • Hybrid or remote work arrangement with periodic trips to headquarters in Mountain View, California.

Categories

Data EngineeringML Engineering
Corvus Robotics

About Corvus Robotics

11-50 employees

Corvus Robotics builds autonomous drones and software that scan, count, and track palletized inventory for warehouses and distribution centers. Its systems perform cycle counting and deliver real-time inventory data to supply chain, retail, and 3PL operators, improving safety and labor efficiency. Founded in 2017 and headquartered in San Francisco, the privately held company reports deployments at large U.S. enterprises and is scaling installations across hundreds of facilities.

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