AI Data Engineer

As a Data Quality Engineer at our company, you will play a crucial role in ensuring the quality and reliability of data used in ML/AI and Generative AI products. Your responsibilities will include: - Performing thorough Data Analysis to evaluate Data Quality, test Machine Learning Models & Visualizations, detect outliers, and use statistical methods to define and monitor valid data ranges. - Collaborating with data scientists, engineers, and product managers to understand the data needs and requirements of different AI applications. - Developing an automation strategy to create automated tests for validating large data sets across products in our company. - Creating test strategies, test plans, and executing test cases manually and via automation to test data-oriented products and data integrations. - Designing, implementing, and maintaining data validation frameworks and data quality monitoring systems. - Working closely with Scrum team members to clarify requirements, ensure testability and automatability, and provide feedback on design (functional and technical). - Analyzing the potential impact of requirement changes, assessing risks, and advocating for quality in every phase of the development process. - Continuously improving automation coverage and reducing regression cycles. In terms of qualifications, we are looking for someone who brings: - Experience in writing complex queries on large customer data sets. - Familiarity with ML/AI and Generative AI techniques, frameworks, and associated toolchains. - Understanding of statistical analysis and core statistical functions. - Strong hands-on experience working with APIs and API automation. - Excellent communication skills and the ability to drive collaboration across teams. - Experience working in Agile development processes and with offshore teams. Additionally, it would be beneficial if you also have: - A Bachelor's degree in Computer Science, Economics, Statistics, or Mathematics with 3-5 years of experience in Data Testing. - Knowledge in Predictive Analytics, machine learning trade-offs, and model evaluation. - Strong scripting experience with Python, SQL, and tools for data analysis and manipulation.,