Senior Software Engineer in Test (AI/ML)

Location: Hybrid schedule with in-office presence 3 days per week; offices in Sunnyvale, California and Toronto, Canada. Fully remote is not available.

Company

hirify.global builds large-scale AI hardware and infrastructure for high-speed model training and inference.

What you will do

• Architect and own end-to-end test strategies for ML API features, including scalable tests, frameworks, and tooling.
• Lead testing and validation of AI/ML models for accuracy, fairness, performance, and production readiness.
• Drive test automation, benchmark adoption, coverage improvements, and risk-based testing decisions.
• Debug complex issues across distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.
• Identify systemic quality gaps and lead cross-functional initiatives with engineering, product, customer operations, and field teams.
• Mentor junior SDETs and facilitate technical communication across geographically distributed teams and time zones.

Requirements

• 5+ years of relevant experience in software integration, development, or quality engineering.
• Deep automation and programming expertise in one or more of Python, C++, or Go, with the ability to build reusable test frameworks.
• Experience testing compute, machine learning, networking, or storage systems in large-scale enterprise environments.
• Strong debugging experience across distributed and scaled-out deployments.
• Experience leading cross-functional quality initiatives and mentoring engineers.
• Strong written and verbal communication, organization, ownership, and independent project execution skills.

Nice to have

• Hands-on experience with LLM or multimodal training and inference workloads.
• Knowledge of hardware architecture, performance optimization, compilers, and ML frameworks.
• Experience testing distributed systems, cloud infrastructure, security validation, microservices, and orchestration at scale.
• Experience owning quality engineering culture or test infrastructure.

Culture & Benefits

• Opportunity to build AI infrastructure beyond the constraints of GPU-based systems.
• Access to cutting-edge AI research, open-source work, and high-performance computing systems.
• Startup vitality combined with job stability.
• Simple, non-corporate culture that respects individual beliefs.
• Continuous learning, growth, and support in an inclusive work environment.