QA Engineer Machine Learning

hace 9 horas

Ciudad de México, Ciudad de México AppIQ Technologies A tiempo completo

AppIQ Technologies is seeking a meticulous and strategic QA Engineer / Sr. QA Engineer to ensure the quality and reliability of our Machine-Learning-driven e-commerce funnel optimisation and digital advertising platform.

You will be responsible for defining the testing strategy for high-performance applications that leverage our proprietary Predictive AI solutions.

As a key member of our fast-paced startup, you will balance the need for rapid feature deployment with the necessity of thorough testing. You will be responsible for identifying and prioritising the highest-risk bugs to ensure our scalable services, which manage millions of daily events, remain robust and accurate.

  • QA Architecture & Strategy: Develop and maintain a comprehensive QA architecture that supports full-stack applications and complex microservices.
  • Risk Management: Prioritise bug fixes based on risk of failure and potential impact, while striking a productive balance between speed-to-market and exhaustive testing.
  • Test Management: Utilise test case management (TCM) systems such as TestRail, Zephyr, Xray, PractiTest, qTest, or similar to organise test cases, track execution, and provide transparent reporting on quality metrics.
  • Automated Testing: Design, implement, and scale automated test suites using tools such as Playwright, Cypress, and Appium.
  • Testing & Validation: Perform rigorous unit tests and integration tests on applications built with TypeScript, React, , Python, and PySpark.
  • Infrastructure Testing: Verify the reliability of deployments across AWS (EC2, S3, Firehose) and Cloudflare edge environments.
  • Data Integrity: Collaborate with Data Engineers to validate the accuracy of complex event data and real-time reporting dashboards.
  • Cross-Functional Collaboration: Act as a great team player with excellent communication skills, working closely with developers and data scientists to ensure a seamless end-user experience.

Requirements

  • 4+ years of professional experience in software quality assurance or engineering, with a strong focus on scalable web applications (7+years for Sr. QA Engineer).
  • Strong grasp of QA architecture and modern testing methodologies.
  • Deep expertise in the tech stack used by our engineers, specifically TypeScript, React, , Python, and PySpark.
  • Cloud & Database Proficiency: Familiarity with AWS services and both SQL and NoSQL (e.g., MongoDB) databases to effectively test data persistence and performance.
  • Global Collaboration: Ability to work effectively with globally distributed teams.
  • Native or Business-level proficiency in written and spoken English

Strong plus if you also have:

  • AI/ML Literacy: Understanding of Machine Learning (Supervised/Reinforcement Learning), Predictive AI, and the validation of Data Pipelines.
  • Proficiency in Python or experience with PySpark.
  • Prior experience in the e-commerce or Ad Tech ecosystem (DSPs, Audience Data, Fraud detection).

Benefits

  • The opportunity to shape the QA culture and architecture from the ground up.
  • An attractive career path on either a management or an individual contributor track.
  • Genuine learning, training and development opportunities, supported by regular performance reviews
  • Competitive compensation and generous paid time off.
  • Work-from-anywhere flexibility
  • Opportunities to develop expertise in building cutting-edge predictive AI applications.

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