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AI and Machine Learning Intern (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
Singapore
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
AI and Machine Learning Intern (AI): Designing and implementing machine learning models, analyzing large datasets, and developing scalable ML pipelines for production environments with an accent on model performance, accuracy, and efficiency. Focus on experimenting with machine learning techniques, integrating models into products, and monitoring deployed solutions.

Location: Hybrid in Singapore, Central Singapore; work from an HPE office an average of 2 days per week.

Company

hirify.global is a global edge-to-cloud company developing solutions that connect, protect, analyze, and process data and applications.

What you will do

  • Design, develop, implement, optimize, and fine-tune machine learning models and algorithms for complex business problems.
  • Preprocess and analyze large datasets to extract insights and prepare data for modeling.
  • Collaborate with data scientists, software engineers, and product managers to integrate machine learning solutions into products.
  • Develop and maintain scalable ML pipelines and infrastructure for production model deployment.
  • Conduct experiments, evaluate machine learning techniques, and monitor and troubleshoot deployed models.
  • Document models and processes and communicate findings through reports, presentations, and visualizations.

Requirements

  • Currently enrolled in university.
  • Available to commence in January 2027.
  • Able to commit to a minimum of 5–6 months full time.
  • Knowledge of machine learning, deep learning, and generative AI.

Culture & Benefits

  • Hybrid work arrangement with an average of 2 days per week in an HPE office.
  • Comprehensive health and wellbeing benefits supporting physical, financial, and emotional wellbeing.
  • Personal and professional development programs supporting career growth and opportunities across divisions.
  • Inclusive work environment that values varied backgrounds and individual uniqueness.

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