Internship- Junior SW Customer Engineer

Wistron Neweb CorpBranchburg, NJ
19d

About The Position

尖端寬頻無線通訊的領導者 邀請您加入共創無限的啟碁. 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.
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