Junior Software Development Engineer in Test (SDET)

Location: Hybrid, with in-office presence three days per week; fully remote work is not available. Office locations: Sunnyvale, California, or Toronto, Ontario.

Company

hirify.global builds AI hardware and software infrastructure designed to accelerate model training and inference beyond traditional GPU-based systems.

What you will do

• Develop, run, and maintain automated tests for AI models, inference features, system behavior, integrations, regressions, and releases.
• Build Python, Go, or similar software for test automation, diagnostics, testbeds, data analysis, dashboards, qualification workflows, and release pipelines.
• Execute cross-stack end-to-end workflows and collect unit, simulation, benchmark, feature-test, and integration evidence.
• Triage regression and rollout failures, reproduce issues, identify owners, validate fixes, and verify closure across master and release branches.
• Collaborate with Integration, Core Infrastructure, feature teams, and release owners to improve coverage and coordinate rollouts.
• Document test intent and findings while growing toward independent ownership of a test domain.

Requirements

• Strong software-engineering fundamentals and programming ability in Python, Go, or a similar language.
• Experience building, testing, or debugging software through internships, research, academic projects, open source, personal projects, or professional work.
• Basic understanding of data structures, algorithms, operating systems, networking, or distributed systems.
• Ability to analyze complex system behavior, form hypotheses, gather evidence, and investigate unexpected results.
• Willingness to read unfamiliar code, learn new stack layers, and take ownership with guidance.
• Clear communication, collaboration, persistence, and comfort working through ambiguity.

Nice to have

• Coursework or project experience in testing, distributed systems, operating systems, compilers, computer architecture, AI systems, or infrastructure.
• Experience with automated tests, test frameworks, CI workflows, developer tools, or data-analysis scripts.
• Exposure to hardware accelerators, software/hardware co-design, low-level systems, or performance debugging.
• Familiarity with AI infrastructure, model deployment, LLMs, multimodal workloads, containers, or cloud environments.
• Experience using logs, metrics, debuggers, profilers, or observability tools to investigate failures.

Culture & Benefits

• Work on an AI platform and specialized hardware designed to accelerate inference.
• Opportunities to engage with AI research, model releases, and open-source work.
• Startup vitality combined with job stability and a non-corporate work culture.
• Continuous learning, growth, and support within an inclusive and diverse workplace.