Software Engineer, QA
Role details
Job location
Tech stack
Job description
We are seeking a skilled and proactive QA Engineer to join our team and ensure the reliability, accuracy, and robustness of our AI-powered products. In this role, you will design and execute test strategies for our applications, APIs and machine learning models. Your work will involve automated testing, edge-case analysis, and collaboration with cross-functional teams to deliver seamless, high-quality user experiences. If you thrive in a dynamic environment and are passionate about quality in AI systems, this is a perfect opportunity to make a tangible impact.
What you will do
Test Automation: Develop automated test suites to validate app features, APIs, and model integrations, ensuring end-to-end reliability and user experience.
Edge Case Analysis: Collaborate with PMs and other stakeholders to identify and rigorously test edge cases, improving the robustness of both platform features and models.
Quality Platform Development: Contribute to building tools and frameworks that enable more efficient and scalable quality testing processes across the organization.
Release Readiness Validation: Implement pre-release quality gates to validate models, APIs, and platform updates, providing a green light for production releases.
Systematic QA Campaigns: Design and lead comprehensive quality assurance campaigns, including functional, stress, and performance testing, to proactively identify potential issues.
Requirements
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You have proven ability to create and execute comprehensive test strategies, covering functional, regression, and exploratory testing for AI products.
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You are proficient in QA tools like Playwright, Postman, or similar platforms for API and functional testing.
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You're skilled in identifying, documenting, and collaborating with developers to resolve issues efficiently.
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You are autonomous and a self-starter.
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You are a proactive problem-solver with a continuous improvement mindset.
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You are proficient in Python or Typescript.
Now it would be ideal if you have :
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Experience testing Machine Learning models.
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Understanding of the Machine Learning lifecycle.
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Experience in various types of testing : performance, load, accessibility or others
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Strong debugging skills.