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At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.
This is the job
In Argentina within the Data industry, we are actively seeking a professional to strengthen our team dedicated that creates targeted video ad placements, and selects individual videos, ensuring brands can safely and effectively scale their video ad campaigns based on unique brand preferences.
This is the team
In your role you'll become a vital member in a team of skilled professionals, including lead the testing of our AI-based products and Enterprise Data Platforms.. Your primary responsibility will involve lead quality assurance initiatives for AI/ML-based applications and enterprise data platforms and design, develop, and maintain automated testing frameworks using Python. Here you will have the opportunity to make a meaningful contribution to global technological progress while at the same time advancing your own skills, and career.
This is you
- Advanced English
- 7-8 years of experience as a Senior/Staff Quality Assurance (QA) Engineer or SDET in complex data-driven environments.
- Strong programming and automation skills in Python and SQL.
- Experience testing data-intensive applications and AI/ML models.
- Hands-on experience with databases such as Postgres and data warehouses such as Snowflake.
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Proven ability to lead QA efforts and advise engineers on best practices.
- Experience working in cross-functional teams, including data science, engineering, and product.
- Familiarity with CI/CD pipelines and test automation tools.
- Knowledge of fairness, explainability, and AI model validation techniques.
- Experience with version control systems (VCS) such as GitHub or GitLab.
- Hands-on experience with PyTorch, NumPy, and Pandas for data validation.
- Experience with Google Gemini and Vertex AI for evaluating AI models.
- Knowledge of Looker and LookML for validating data analysis.
- Knowledge of CI/CD pipelines and test automation frameworks for ML workflows.
- Experience with AdTech or data-intensive applications.
- Lead quality assurance initiatives for AI/ML-based applications and enterprise data platforms.
- Design, develop, and maintain automated testing frameworks using Python.
- Develop and execute comprehensive test plans for ML models, ensuring accuracy, fairness, and robustness.
- Validate data pipelines and ETL processes, working with Postgres, Snowflake, and Looker.
- Collaborate with data engineers, ML engineers, and product teams to define quality metrics.
- Identify, analyze, and document defects, ensuring timely resolution.
- Establish best practices for QA automation, CI/CD pipelines, and test data management.
- Mentor and mentor junior QA engineers, fostering a culture of quality.
Key Skills
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