Based on decades of parallel computing research at MIT, Neural Magic has developed deep learning model sparsification tools and a CPU inference engine.

Our solution helps data scientists and ML engineers sparsify and quantize deep learning models to minimize footprint and run on CPUs at GPU speeds. Please look through our GitHub repos to get a feel of what we are about, and if still interested, apply to join our team.

We are looking for a Software Engineer in Test to work closely with our Development, Machine Learning and Product teams to test and validate our cutting-edge Machine Learning Engine and its UI components.

You will be responsible for designing and implementing test cases from back-end to front-end and automating test executions for the product. A main focus of this role will be testing the UI components of the product through web interfaces and the RESTful APIs, and creating automations to execute the test cases. You will also be involved in the end-to-end testing of the product in different environments including different operating systems, docker, AWS EC2 etc.

Responsibilities

• Create comprehensive test plans and cases to meet product requirements.
• Perform thorough functional, performance, regression testing to ensure product quality.
• Implement test code and build automation to execute test cases.
• Monitor test results, report test status and analyze failures.
• Keep improving test framework and cases to provide better coverage and execution for the product.

Requirements

• Proven record (3+ years) of software testing experience with excellent quality.
• Proactive, dedicated and have a sense of ownership.
• Good knowledge of software testing methodologies, tools and processes.
• Strong experience in web application testing, automation and the toolsets such as Selenium, Protractor, Postman etc.
• Programming skills in Python, Java, C/C++ etc.
• Familiar with Linux/Unix systems and experience in scripting.
• Experience in setting up CI/CD processes in AWS is a plus.
• Experience in Machine Learning especially Deep Learning is a plus.
• BS/MS degree in Computer Science, Engineering or a related subject.