Responsibilities:
Understanding how all elements of the ML software ecosystem work together and developing QA approaches/frameworks that fit the overall strategy
Responsible for development of test strategies and creation of appropriate ML test harnesses for AI Inference Accelerator Cards
Providing test infrastructure to enable engineering teams to test and deliver functional/performance metrics
Ensure ML features are planned, validated, and automated as per release and customer requirements
Development and execution of test plans, monitoring and reporting on test execution and quality metrics. Debug feature and unit/system level defects
Strong hands-on automation skills to enable onboarding of automated features into the test framework
Basic Qualifications
Bachelor’s Degree in Computer Science or related field experience
4+ years relevant work experience
Hands on experience in at least, one or more modern programming language such as Python (mandatory), Shell, C++
Strong experience in various software technologies, methodologies and applied software engineering practices/standards such as Object-Oriented Design (OOD), cloud and embedded software test automation
Preferred Qualifications
Excellent programming skills in one or more programming languages (Python, Bash, C++)
Hands-on experience in API testing & developing automation test scripts for Embedded/IOT Platforms
Familiarity with AI frameworks models performance, quantization and accuracy metrics
Experience with ML frameworks such as PyTorch, Caffe2, Tensor flow etc and HW accelerators
A deep understanding of automation testing and experience in writing automation scripts/programs that will aid in automated testing.
Minimum Qualifications
Education:
Bachelors - Computer Science, Bachelors - Engineering, Bachelors - Information Systems
Work Experiences:
5+ years of Systems engineering or related work experience.
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