QA Engineer for Machine Learning

Elastic is the world's leading software provider for making structured and unstructured data usable in real time for search, logging, security, and analytics use cases. Founded in 2012 by the people behind the Elasticsearch, Kibana, Beats, and Logstash open source projects, Elastic's global community has more than 80,000 members across 45 countries, and since its initial release. Elastic's products have achieved more than 100 million cumulative downloads.

Elastic is seeking a talented Quality Assurance Engineer to join our Machine Learning team. You will have the opportunity to work with exceptional engineers on cutting edge technology in a small and focussed team. You can and learn and build your skills as a QA Engineer whilst working on both manual and automated testing for our ML products. The ML team works on features that form a natural extension to the search and analytics capabilities in Elasticsearch by focussing on providing “Time Series Anomaly Detection” capabilities using unsupervised machine learning. Over time we plan to add more machine learning capabilities, but for now we are focused on providing added value to users storing time series data such as log files, application and performance metrics, network flows, or financial/transaction data in Elasticsearch. Machine Learning is part of our X-Pack.

• Participate in all aspects of QA product lifecycle: Scoping, test case creation and maintenance, feature, regression, integration /end-to-end test execution and automation
• Report and verify bugs in a timely manner
• Ability to identify and research issues with our products
• Communicate status and escalate issues in a timely fashion
• Construct test cases for the defined test plan; modify the existing test cases as the test requirements change
• Identify and develop areas for automation
• Build test environments
• Provide input/status updates regarding test progress/results on a daily basis
• Operate under minimal supervision

What you will bring

• 2+ years of manual software test experience
• Good knowledge of QA methodologies
• Experience of QA automation
• Experience testing data visualization or data analytics products
• Experience using bug tracking software
• Good knowledge of scripting languages
• Working knowledge of Linux and/or Windows operating systems
• Good numeracy, demonstrable mathematical or statistical background
• Ability to work independently; following tasks assigned and seeking guidance when needed
• Flexible, “can do” approach, able to adjust to changing priorities and willing to help out in other functional areas
• Attentive to detail and highly organized

Nice to Have

• Experience deploying AWS resources for test environments
• Experience testing REST APIs
• Mathematical / statistical / engineering degree