Staff Engineer, Test Automation (AI)

Location: San Diego, California, United States. Workplace: On-site.

Company

hirify.global is a venture-backed defense technology company developing intelligent systems, including autonomy software, unmanned aircraft, and simulation and synthetic reality technologies.

What you will do

• Own the technical strategy, architecture, and roadmap for automated testing, verification, and MLOps quality across the autonomy software ecosystem.
• Design scalable test frameworks for autonomy software, backend services, APIs, operator applications, and distributed hardware environments.
• Lead functional, integration, regression, performance, reliability, and end-to-end testing across simulation, edge-compute, software-in-the-loop, and hardware-in-the-loop environments.
• Build automated machine learning validation pipelines covering data quality, training reproducibility, model accuracy, robustness, latency, and deployment integration.
• Establish CI/CD and continuous-training workflows with versioning and traceability for datasets, models, configurations, evaluation results, and deployment artifacts.
• Develop scenario-based validation, observability, analytics, failure triage, test harnesses, simulators, mocks, and synthetic data capabilities.

Requirements

• Typically 8+ years of relevant experience in software engineering, test infrastructure, developer tooling, MLOps, systems integration, or systems verification.
• 5+ years building scalable automation frameworks or developer tooling in Python, including asynchronous and concurrent programming.
• Experience designing test, CI/CD, or MLOps infrastructure used across multiple engineering teams.
• Experience validating machine learning systems across data, training, evaluation, packaging, deployment, and monitoring, including data leakage, drift, nondeterminism, and model regression risks.
• Experience testing GPU-accelerated workloads and multi-tenant Kubernetes environments, including scheduling, resource allocation, isolation, quotas, and observability.
• Strong system-design skills and experience testing distributed systems, backend services, APIs, integrated hardware and software, reproducible environments, and Linux-based development systems.

Nice to have

• Experience with MLflow, Kubeflow, Weights & Biases, SageMaker, Vertex AI, model serving, experiment tracking, and artifact promotion.
• Experience with NVIDIA GPU infrastructure, CUDA, GPU scheduling, profiling, and performance-analysis tools.
• Experience validating autonomy, perception, planning, decision-making, reinforcement learning, embedded, or edge-compute systems.
• Experience with reliability, fault-injection, recovery testing, air-gapped environments, containers, infrastructure as code, or reproducible test environments.
• Proficiency with Go or TypeScript, or experience integrating Python with native C or C++ applications.

Culture & Benefits

• Work on intelligent systems for unmanned aircraft and robotic platforms operating in complex, contested, and GPS-denied environments.
• Collaborate across software, autonomy, machine learning, data, simulation, and systems engineering disciplines.
• Develop AI-assisted engineering workflows using coding agents and LLM-based tools while maintaining security, reproducibility, and traceability.
• Work as part of the Hivemind Enterprise Division's Quality organization in an on-site environment.