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Home   QA Engineer SUELDO EN USD

Empresa:

AHRENS&ASOC

Industria:

RRHH

Ubicacion:

Hidalgo 355, Capital Federal, Argentina
Postularse

QA Engineer SUELDO EN USD

AHRENS&ASOC

Modalidad: Trabajo Remoto

Remuneracion: $5.000 / $7.000

Lugar de Trabajo: Desde Casa

Do you believe ensuring that AI models are available and working correctly is even more critical than other software?  Are you interested in joining a startup early enough to really innovate while building on a wave of already proven success?  Would you like to be part of an AI movement seeking independence from big toy workbenches and cloud roadmap promises?

What You Will Do

As a QA Engineer on our team, you will be creating test cases to validate acceptance criteria for new features, executing them manually or automating them as regression candidates.  You will help manage independent test batteries designated for different stages of the development lifecycle, and to leverage configuration management tools to emulate environments for regression of new versions and patches.  You will also partner with data scientists to understand the typical business performance metrics and service level objectives commonly established for different types of algorithms, helping to create synthetic data sets to thoroughly test advanced model performance metrics, and to validate our methods for ensuring the quality, reliability, and accurate detection of model degradation.

What Would Help Us

  • Someone with 3 to 5 years of full-time test automation with primary focus on Python or JavaScript
  • Insight into how blackbox, smoke, and integration cases combine to provide effective coverage
  • Being able to understand and manage your own infrastructure to rule out environmental false positives
  • Ability to quickly grasp functional changes and come up with a corresponding set of test cases
  • Testing of multi-tenant applications and other SaaS considerations
  • Ability to validate test results by gathering data from tables and logs with automation
  • Some familiarity with validating data quality, testing ETL processes, and other data engineering
  • Of course, experience with ML or testing ML-based applications is great, but not required
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