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

Agility Robotics

full-time

Posted on: 9/3/2025

Location: Oregon • 🇺🇸 United States

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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.

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.