AI/ML TESTER
Posted Updated
Summary
Tests AI/ML and LLM-based systems and big-data pipelines for quality, accuracy, and performance. Writes test cases in SQL and Python and works with Databricks, PySpark, Apache Spark, and Pandas to validate data transformations, storage, and retrieval across the development lifecycle.
Summary
We are seeking a skilled AI/ML Tester to join our IT Services team, where you will play a pivotal role in ensuring the reliability and performance of advanced data and machine learning solutions. This position is critical for validating complex data pipelines and workflows, ensuring that AI and LLM-based systems deliver high-quality results. The ideal candidate will possess a strong background in testing methodologies specific to data engineering and artificial intelligence, bridging the gap between development and deployment to maintain system integrity.
Responsibilities
- Execute comprehensive testing strategies for data pipelines, focusing on data quality assurance and integrity across various stages of the workflow.
- Validate the functionality and performance of AI/ML models and LLM workflows, ensuring they meet defined business requirements and accuracy standards.
- Design and implement test cases using SQL and Python to verify data transformations, storage, and retrieval processes.
- Conduct rigorous testing on big data frameworks, specifically utilizing Databricks, PySpark, and Apache Spark to ensure scalability and efficiency.
- Leverage Pandas and other data manipulation libraries to analyze datasets and identify anomalies or discrepancies.
- Collaborate with development teams to troubleshoot issues within the data ecosystem and recommend improvements for system robustness.
- Monitor and assess the overall health of data quality metrics throughout the software development lifecycle.
Requirements
Requirements:
- Possess 3 to 4 years of professional experience in software testing, with a specialized focus on data and AI/ML domains.
- Demonstrate proficiency in SQL for querying databases and validating data integrity.
- Have hands-on experience with Python programming for scripting, automation, and data analysis.
- Show proven expertise in testing data pipelines and ensuring data quality within large-scale environments.
- Be familiar with Databricks, PySpark, Pandas, and Apache Spark technologies.
- Possess practical exposure to AI/ML workflows or Large Language Model (LLM) testing processes.
- Hold a salary expectation aligned with the market rate of ₹10 LPA.