
QA Engineer(AI/ML focus) - Remote
- Córdoba
- Permanente
- Tiempo completo
- Design and implement AI-driven quality checks: build models to detect anomalies, identify schema drift, and classify data errors in real time.
- Automate and scale QA: replace manual and rule-based validation with ML-powered solutions that continuously improve.
- Leverage GenAI for validation: use embedding models, LLMs, and prompt-driven pipelines to perform semantic checks on scraped data.
- Develop monitoring & alerting pipelines: quantify data quality via KPIs, dashboards, and automated reports for stakeholders.
- Experiment & innovate: research and prototype new AI techniques for QA, e.g. using embeddings, synthetic data, and reinforcement learning to stress-test scrapers.
- Collaborate cross-functionally: work with developers, product managers, and account teams to integrate AI-based QA into production workflows.
- Communicate insights: present findings with clear visualizations, metrics, and evidence-based recommendations to technical and non-technical audiences.
- Proficiency in Python & PyData stack (NumPy, pandas, scikit-learn, PyTorch/TensorFlow preferred).
- 3+ years in a data science, applied ML, or data engineering role (ideally with exposure to QA or data validation at scale).
- Hands-on experience with GenAI tools: LLM APIs (OpenAI, Anthropic, Google), prompt engineering, cost/token optimization.
- Strong ML fundamentals: anomaly detection, classification, clustering, embeddings, evaluation metrics.
- Experience with big data frameworks (Spark, BigQuery, or similar).
- Ability to work with very large datasets (millions+ of records).
- Version control skills (GitHub/Bitbucket).
- Excellent communication in English, both technical and non-technical.
- Prior experience in data quality automation or web data QA.
- Familiarity with LangChain, MCP, Marvin, or similar orchestration frameworks.
- Experience building QA dashboards or visualization layers.
- Background in statistics or applied mathematics.
- Previous remote/distributed work experience.