ML Test and Automation Engineer

Job Area: Engineering Group, Engineering Group > Software Test Engineering

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Test Engineer, you will design, develop, create, and modify test cases and validate embedded software, cloud software, system algorithms, application software, automation, and/or specialized utility programs that launch cutting-edge, world class products. Qualcomm Software Test Engineers collaborate across various engineering teams and functions to design and implement test plans.

Minimum Qualifications:

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Test Engineering or related work experience.

OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Test Engineering or related work experience.

OR
PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Test Engineering or related work experience.

2+ years of work or academic experience with Software Test or System Test, developing and automating test plans and/or tools (e.g., Source Code Control Systems, Continuous Integration Tools, and Bug Tracking Tools).

As a hands-on ML Test and Automation Engineer, you will be responsible for improving efficiency and approach to testing. Working backwards from customer needs, you will identify the right sets of tools to build to achieve the best quality and customer experience. You will participate and lead test automation efforts for critical and complex project requirements. You will be responsible for driving improvements in test tools, test environments and reporting mechanisms as well as influence the implementation of the right solutions.

As a member of the Test engineering team, you will own the vision for test infrastructures, build automation frameworks that allow developers to easily write reliable tests, and invent new mechanisms for ensuring that every change we make can be deployed safely and quickly.

The ideal candidate for this role has a strong track record and proficiency in building efficient and innovative test tools. A logical problem-solver with good judgment who brings an experienced perspective to balance quality and strategy trade-offs to meet the needs of the AI Inferencing Team

They have specialized knowledge analyzing test procedures, inspecting architectures, and developing test infrastructure and tools that provide high confidence in product quality.

Responsibilities:

Understanding of the ML software ecosystem and QA approaches/frameworks

Strong fundamentals of Deep learning, transformer architecture, industry-grade LLM serving KPIs

Responsible for development of test strategies and ML test harnesses for AI Inference Accelerators

Create automated test infra to for engineering teams to test and deliver key features

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

Working knowledge of performance engineering aspects for LLM serving systems

Basic Qualifications

Bachelors Degree in Computer Science or related field experience

4+ years relevant work experience

Hands on experience in at least, one of Python (mandatory), Shell, C++

Strong experience in software technologies, methodologies, and applied software engineering practices 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

Deep understanding of automation testing and writing automation scripts

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