Solvd is an AI-first advisory and digital engineering firm delivering measurable business impact through strategic digital transformation. Taking an AI-first approach, we bridge the critical gap between experimentation and real ROI, weaving artificial intelligence into everything we do and helping clients at all stages accelerate AI integration into each process layer. Our mission is to empower passionate people to thrive in the era of AI while maintaining rigorous ethical AI standards. We’re supported by a global team with offices in the USA, Poland, Ukraine and Georgia. We are looking for a Data QA Engineer to join our growing team.

Responsibilities:

• Sense of ownership of the QA process and product quality.
• Develop comprehensive test plans and test strategies specific to the client's AI/ML Platform and AI/ML models.
• Test AI/ML models at different stages of development to identify errors, points of failure and ensure accurate results.
• Design and implement AI/ML-based test automation.
• Analyze and interpret test results to provide recommendations for issue resolution and improvements.
• Monitor bug resolution efforts and track to ensure timely issue resolution.
• Collaborate closely with developers to identify and troubleshoot issues during the development process.
• Utilize AI/ML debugging, profiling tools to assist in testing, issue identification.
• Collaborate with ML Engineers and Product Managers to deeply understand the user experience and product context of ML product features under test.
• Work closely with ML Engineers to understand the structure, characteristics, and intended use of the datasets created for machine learning tasks.
• Use SQL knowledge for data testing, getting data from databases, comparing data sets.
• Detect and document data quality issues, including inaccuracies, inconsistencies, and anomalies, and work collaboratively to troubleshoot and resolve them.
• Driven by results - have the pragmatic urgency to resolve blockers, unclear requirements and eventually make things happen. Improve data, test and automation coverage by continuously reviewing customer issues and usage patterns.

Mandatory requirements:

• 5+ years of building QA infrastructure or test cases as a Quality Engineer or Quality Assurance Engineer.
• Strong knowledge of software QA methodologies, tools and processes.
• Experience in writing clear, concise and comprehensive test plans and test cases.
• Hands-on experience with SQL for data querying and analysis, and data set creation.
• Hands-on experience with data testing.
• Strong understanding of database systems, data structures, and data manipulation techniques.
• Experience working in an Agile/Scrum development process.
• Experience with performance and/or security testing is a plus.
• BS/MS degree in Computer Science, Engineering or a related subject.
• Team player and ability to "roll up your sleeves" and do what it takes to make the team successful while leveraging your leadership skills to coach, train, and mentor less experienced Professional Services team-members.
• Hands-on experience with both white box ie at least one scripting language like Java, Python, etc. and black box testing.
• Excellent communication and collaboration skills, ability to work with cross functional teams.
• Strong problem solving skills, very detail oriented.
• Ability to work independently.

Optional requirements:

• Computer Science, ML or related field with QA experience in AI/ML models.
• Experience with testing and automation tools for validating AI/ML Models.
• Proficiency in Python or Java.
• Experience working with orchestration platforms.
• Experience collaborating with data science teams and leveraging their datasets in a testing environment.