As a Machine learning QA engineer, you will work closely with the Product Management, Data scientistand ML Analyst to understand the ML algorithm requirements. You will be working on identifying the ML test strategies and automating the test scenarios for complex ML workflows. The successful ML-QA has strong technical aptitude and strong desire to learn new technologies, have agile approach.
- Understanding of machine learning techniques, data structures, algorithms, statistics.
- Proficient in designing, understanding and implementing algorithms
- Drive improvements in the existing automation framework to improve quality and maintainability.
- Develop and maintain domain, product and process knowledge to directly influence the product quality, software engineering productivity and development process maturity
- Define, improve and automate metrics collection and reporting
- Drive test effectiveness and efficiencies throughout the team
- Drive research of industry trends and apply best practices in quality engineering practices used in evolving machine learning techniques.
- Keep current on new technologies and make recommendations on future direction for quality engineering as well as apply latest techniques and industry information as appropriate.
- Good understanding of designing part of scalable and maintainable automated testing solutions for large scale systems
- Demonstrated ability to learn and apply new technology, tools and process
- Excellent English written and verbal communication skills
- Demonstrated collaborative and mentoring skills
- Knowledge of agile environment