Agility Robotics

Staff Machine Learning Engineer – A&P/Infrastructure/Data Platform

Agility Robotics

full-time

Posted on:

Origin:  • 🇺🇸 United States • Oregon

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Job Level

Lead

Tech Stack

AirflowAWSAzureCloudGoogle Cloud PlatformTerraform

About the role

  • Architect and build the foundational ML infrastructure layer on top of the core data platform to power fleet-scale humanoid robotics.
  • Define a long-term vision for ML infrastructure aligned with company goals and industry best practices.
  • Deliver a roadmap for development of a level 2 MLOps platform after consulting with researchers and perception engineers.
  • Partner with data platform engineers to integrate ML workflow orchestration and tracking systems with existing data platform tooling.
  • Design and implement ML development environments, including secure, scalable workspaces for interactive experimentation (JupyterHub etc.).
  • Develop core infrastructure including a model registry, feature store, and experiment tracking tooling.
  • Define CI/CD lifecycle for ML enabling continuous retraining, automated testing, and seamless model delivery to production.
  • Drive adoption of MLOps best practices: reproducibility, lineage, rollback, monitoring, and governance.
  • Mentor junior engineers and influence the cloud platform organization’s roadmap.
  • Lead greenfield, zero-to-one efforts to define company-wide ML infrastructure.

Requirements

  • 8+ years of software engineering experience or ML infrastructure experience with a demonstrated track record of building data platforms and MLOps pipelines.
  • Expertise in modern data platform technologies.
  • Significant experience with ML frameworks and orchestration tools (MLflow, WandB, Airflow, Kubeflow, etc.).
  • Strong proficiency with cloud-native tooling (AWS, GCP, or Azure), containers, and IaC (e.g., CDK, Terraform).
  • Experience working cross-functionally with ML, data, and platform teams.
  • Ability to mentor junior engineers and influence broader platform roadmaps.
  • Bonus: Experience with robotics, autonomous vehicles, drones or embedded ML.