Role Overview
You will be part of a team responsible for
bringing a software stack to production for next-generation AI compute platforms. As a member of the
Software QA team, you will design and build
automated test frameworks for AI hardware and software components, and continuously enhance the
test and qualification infrastructure to support evolving products.
This role involves leveraging
CI/CD pipelines and Python-based test frameworks to drive both
component-level and end-to-end validation. You will develop automation to support
large language model accuracy, benchmarking, and robustness testing, ensuring software and hardware stacks meet high quality and performance standards.
You will collaborate closely with
machine learning kernel teams, compiler and runtime engineers, hardware architects, and ML researchers across global teams throughout the qualification lifecycle. There will also be opportunities to contribute to
emerging ML and AI technologies as part of the broader engineering effort.
Qualifications
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field, with 7+ years of industry experience.
- Solid understanding of machine learning fundamentals and large language models.
- Strong proficiency in Python, including data structures, and experience working in a Linux environment.
- Self-driven team player with strong collaboration skills.
Preferred Experience
- Experience working in startups or small, fast-paced teams.
- Hands-on exposure to machine learning models and neural network layers.
- Experience testing deep learning frameworks such as TensorFlow, PyTorch, and transformer-based models.
- Familiarity with CI/CD systems, particularly GitLab-based pipelines.
