Staff Automation Test Engineer for Autonomy & MLOps

InvestedintheMission; San Mateo (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity

Benefits

Full-time regular employee offer

Job summary

Shield AI is seeking a Staff Automated Test Engineer to lead automated verification across its Hivemind autonomy platform. You will define test architecture, validation infrastructure, and CI/CD pipelines to enable resilient autonomous systems for unmanned aircraft and robotics.

The role spans production flight code, ML models, simulation, data pipelines, and ground control applications, requiring deep Python automation and scalable testing across diverse environments.

Qualifications

• Typically 8+ years of relevant experience in software engineering, test infrastructure, or ML/AI verification.
• 5+ years building scalable automation frameworks or developer tooling in Python.
• Experience validating ML systems across data, training, evaluation, deployment, and monitoring lifecycle.

Responsibilities

• Own the technical strategy, architecture, and roadmap for automated testing, verification, and MLOps quality across the Hivemind ecosystem.
• Design and maintain scalable test frameworks for autonomy software, backend services, APIs, and distributed hardware environments.
• Lead functional, integration, regression, system, performance, reliability, and end-to-end testing across simulation, edge-compute, and hardware-in-the-loop environments.
• Build automated ML validation pipelines covering data quality, training reproducibility, model accuracy, robustness, and latency.
• Establish CI/CD and continuous training workflows with versioning of datasets, models, configurations, and evaluation results.

Skills

Python

Test automation

MLOps

Distributed systems testing

Linux

CI/CD

Automation frameworks

Tools

Conan

pip

setuptools

Poetry

Nix

Kubernetes

NVIDIA Nsight

Job description

Shield AI is seeking a Staff Automated Test Engineer to lead automated verification across its Hivemind autonomy platform. You will define test architecture, validation infrastructure, and CI/CD pipelines to enable resilient autonomous systems for unmanned aircraft and robotics.

The role spans production flight code, ML models, simulation, data pipelines, and ground control applications, requiring deep Python automation and scalable testing across diverse environments.