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Data And Machine Learning Intern

Формат работы
remote (Colombia)
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
Colombia
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
Data and Machine Learning Intern: Assist in designing, developing, and maintaining data pipelines and implementing ML systems following best practices. Focus on integrating data from various sources, understanding business objectives, and implementing ML systems.

Location: Colombia; fully remote and globally distributed team

Company

hirify.global delivers GenAI and machine learning projects for companies across multiple industries.

What you will do

  • Design, develop, and maintain data pipelines for clean, reliable, and timely data.
  • Implement and optimize ETL processes and integrate data into warehouses, data lakes, and lakehouses.
  • Clean, validate, transform, explore, and visualize large datasets.
  • Develop metrics and machine learning models aligned with business objectives.
  • Implement systems using classical machine learning, deep learning, and foundation models.
  • Support requirements gathering, client communications, deliverables, and model error analysis.

Requirements

  • Be in the final year of a bachelor's degree in Computer Science or a related field.
  • Proficient English; CV must be submitted in English.
  • Basic knowledge of Python, machine learning, data libraries, and databases.
  • Understanding of statistical, machine learning, and deep learning algorithms.
  • Experience visualizing and manipulating large datasets.
  • Strong problem-solving, curiosity, autonomy, teamwork, adaptability, and dependability.

Nice to have

  • AWS knowledge.
  • PySpark or Spark, Airflow, data lakes, and data warehouses experience.

Culture & Benefits

  • Six-month, paid, full-time internship at 40 hours per week.
  • Remote and flexible work environment.
  • Every other Friday off.
  • Health bonus, paid sick days, and local holidays.
  • Collaborative work with certified specialists, technical experts, and PhDs.

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