Deepgram
Software Test Engineer
About this role
Deepgram seeks a Software Test Engineer to design and maintain automated test frameworks across voice AI APIs, models, and data platforms. You'll build scalable automation, translate product requirements into test strategies, and partner across teams to ensure production systems are robust and reliable.
What you'll do
- Design and build automated test suites for functional, integration, end-to-end, regression, API, and service-level testing across batch and streaming workflows
- Create test plans and strategies aligned with product requirements and customer acceptance criteria, defining clear release gates
- Develop representative and adversarial test datasets, fixtures, and environments that exercise real-world inputs, edge cases, and system limits
- Validate AI-powered features including speech-to-text and text-to-speech using appropriate metrics, human review, and regression coverage
- Build testing infrastructure including test harnesses, dashboards, pipelines, and CI/CD integration to detect regressions continuously
- Partner with Engineering, Product, Research, Data, and DevOps teams to understand system behavior, dependencies, and establish appropriate test coverage
What they're looking for
- Test automation and framework design
- API and integration testing
- CI/CD pipeline integration
- Python, JavaScript, or similar programming languages
- Test data management and fixture creation
- Performance and load testing
- SQL and data validation
- AI/ML model evaluation fundamentals
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Deepgram
Deepgram builds voice AI and speech processing technology, offering platforms that power real-time speech recognition and audio intelligence across cloud, edge, and embedded environments. The company is hiring applied ML engineers, backend engineers, embedded AI engineers, and customer-facing roles (customer success and pre-sales engineers) to scale its AI infrastructure and drive enterprise adoption.
- Website
- deepgram.com
Likely interview questions
- Describe your experience designing automated test frameworks from scratch. What testing tools and languages have you used most effectively?
- How do you approach testing AI/ML-powered features, and what metrics or validation strategies have you found most effective?