Participate in the analysis of requirements, user stories and acceptance criteria for AI/ML-enabled systems, identifying model limitations within the project's targeted context and the impact of the AI’s probabilistic behavior on the final product.
Support the implementation of defined quality strategies for AI/ML projects, considering all stages of model development (data, training pipelines, evaluation, inference, integration and probabilistic behavior).
Assess the quality of splits created in datasets, understanding core concepts of consistency, completeness, representativeness, balance, annotations, data leakage and suitability for the model and system objectives. Evaluate AI/ML models based on the test strategies and metrics defined by the team.
Execute the defined testing strategy considering all functional and non-functional aspects of systems.
Validate end-to-end behavior of AI systems.
Monitor, analyze and report quality metrics related to software, data and models across all versions.
Develop and maintain test automations and automated testing processes using frameworks such as Pytest, Robot Framework, Selenium, Appium, Cypress, JMeter, Artillery or equivalent tools.

Knowledge of the AI/ML development lifecycle, including problem definition, data collection, data preparation, training, validation, testing, deployment, monitoring and retraining.
Understanding of fundamental concepts in machine learning, NLP, computer vision and multimodal models.
Knowledge of model training, validation and testing, including overfitting, underfitting, generalization, data leakage, class imbalance, data distribution, data drift and performance evaluation.
Analytical ability to investigate failures, compare results, identify patterns, propose hypotheses, validate evidence and communicate technical conclusions. Experience with code versioning, preferably with Git, GitLab, GitHub or similar tools.
Basic knowledge of completeness analysis and safety for autonomous robotic tasks.
Knowledge of the Python programming language.
Ability to apply LLMs in the context of test automation for software.
Currently pursuing a degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Statistics or related fields.
Advanced/Fluent English for reading, writing and day-to-day communication with the team and external stakeholders.

Quality of life: 40-hour workweek under CLT employment, flexible schedule with in-office presence;
Well-being: Gympass (WellHub, workplace exercise classes, quick massage and psychological support);
Health: Medical and dental insurance for you and your family;
Children: Childcare assistance for our little SiDiers, 120-day maternity leave and extended paternity leave;
Future: SiDi contributes with you to a private pension plan;
Education: Incentive program for continued studies and specialization, support for SiDiers to become fluent in other languages and weekly lecture series on global trend topics;
Food: Flexible Meal and Food Allowance;
Transportation: Transportation subsidy/allowance to the SiDi office and parking for those working at the office;
Recognition: Annual performance bonus and awards for SiDiers who achieved something outstanding;
Diversity: Committees on Well-being, Diversity, Mental Health, Social issues, Sustainability and Inclusion of women in technology;
Modern Offices: Relaxed and collaborative environments with communal spaces, a decompression room, kitchenette and coffee machine;
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AI/ML Software Test Developer

Key skills