Level: Experienced

Job Field: Data, Test/QA

Employment Type: Full Time

Contract Type: Permanent employment

Salary: from 3.843 € Gross/Month

Location: Linz

Working Model: Hybrid, Onsite

Job Summary

In this role, you will develop automated tests for AI/ML systems and integrate them into CI/CD pipelines, ensuring the quality and performance of models while driving continuous improvement.

Job Technologies

Your role in the team

Design, implement, and maintain comprehensive automated test suites specifically tailored for AI/ML systems, covering unit, integration, and end-to-end scenarios.
Integrate testing workflows into the Continuous Integration/Continuous Delivery (CI/CD) pipelines, managing regression runs and optimizing testing strategies for the unique characteristics of AI components (model performance, latency, and drift).
Apply knowledge of machine learning and statistics to design meaningful validation tests, interpret model outputs, and continuously assess datasets for quality, completeness, and potential bias or drift.
Work closely with Product Owners, Technical Leads, Developers, and AI Engineers to ensure testability is baked into the model design from the start, driving continuous improvement in AI-related QA processes.
Actively contribute to implementing and enforcing responsible AI and ethical principles within the QA framework.

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Our expectations of you

Qualifications

Strong understanding of general QA principles, the Software Development Lifecycle (SDLC), and core machine learning concepts.
Knowledge of key ML evaluation metrics and basic statistical methods (e.g., precision, recall, F1 score, AUC) necessary for interpreting and validating model performance.
You possess strong communication and collaboration skills to effectively bridge the gap between AI Engineers (model builders) and Software Engineers (system builders), driving a unified quality standard.
You are a proactive driver of process improvement, always looking for ways to automate testing, increase coverage, and ensure the reliability and ethical soundness of production models.

Experience

Proven experience in test automation, quality assurance, or software development, with strong proficiency in Python or a similar programming language.
Practical experience with AI evaluation and tracking tools (e.g., MLflow, Weights & Biases) and familiarity with standard automation/CI/CD tools (e.g., Jenkins, GitLab, GitHub Actions).

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