Internship- Junior SW Customer Engineer

Wistron NeWeb Corporation•Milpitas, CA

About The Position

We are a leading company in the wireless broadband communications industry looking for talented professionals with a winning attitude. Job Description Key Responsibilities: Support product technical acceptance and certification process Run product validation, verification and regression to ensure product quality, performance, reliability, usability, durability and conformance that meet the company’s as well as customer’s KPI Ensure high system level product quality/performance and out-of-the box user experience Support, run field test as necessary Manage and monitor all installed systems, maintained automated infrastructure and coordination test house activities Provide and improve automation test items request to improve efficiency and reduce human intervention time Engaging with product group in L2 and L3 level problem escalation Frequent vendors and customer meetings and visits for product feedback and future opportunities Provide technical post-sales support to R&D team Work with R&D and DQA/SQA teams to ensure features delivery/inclusion. Design and implement AI-driven solutions using machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Develop and maintain automation scripts in Python, Bash, or PowerShell to streamline operations and data processing. Collaborate with data scientists and product teams to integrate AI models into production environments. Build APIs and microservices to support AI applications and automation tools. Stay current with emerging technologies in AI, scripting, and software engineering best practices.

Requirements

Bachelor’s or master’s degree in computer science, or related field.
1+ years of experience in software development, with a focus on AI and scripting
Candidate could start with a 3-6 months internship given the right background
Proficiency in Python and at least one other scripting language (e.g., Bash, JavaScript, PowerShell).
Experience with AI/ML frameworks and libraries.
Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
Strong problem-solving skills and ability to work independently or in a team.
Willing and able to travel
Ability to work in a team as well as an individual contributor when necessary
Out of the box thinking.
Critical thinker and problem-solving skills
Strong Chinese/Mandarin knowledge is a plus

Nice To Haves

Experience with MLOps and CI/CD pipelines.
Knowledge of NLP, computer vision, or reinforcement learning.
Contributions to open-source AI projects or published research.
Experience with version control systems (e.g., Git) and agile development methodologies.

Responsibilities

Support product technical acceptance and certification process
Run product validation, verification and regression to ensure product quality, performance, reliability, usability, durability and conformance that meet the company’s as well as customer’s KPI
Ensure high system level product quality/performance and out-of-the box user experience
Support, run field test as necessary
Manage and monitor all installed systems, maintained automated infrastructure and coordination test house activities
Provide and improve automation test items request to improve efficiency and reduce human intervention time
Engaging with product group in L2 and L3 level problem escalation
Frequent vendors and customer meetings and visits for product feedback and future opportunities
Provide technical post-sales support to R&D team
Work with R&D and DQA/SQA teams to ensure features delivery/inclusion.
Design and implement AI-driven solutions using machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Develop and maintain automation scripts in Python, Bash, or PowerShell to streamline operations and data processing.
Collaborate with data scientists and product teams to integrate AI models into production environments.
Build APIs and microservices to support AI applications and automation tools.
Stay current with emerging technologies in AI, scripting, and software engineering best practices.