Machine Learning Engineer

Cape Town FULL TIME R50,000 - R75,000 / Month
(R600,000 - R900,000 / Year)

Job Description

We are in search of a detail-oriented Machine Learning Engineer who possesses a robust understanding of machine learning algorithms and AI methodologies. Your role will involve developing innovative models and solutions that harness the power of artificial intelligence to solve real-world problems. The ideal candidate will have a strong programming background and experience in handling large datasets.

Responsibilities

  • Create innovative machine learning solutions based on business requirements.
  • Conduct experiments to evaluate model performance and accuracy.
  • Ensure compliance with best practices in machine learning and data governance.
  • Coordinate with the software development team for integration.
  • Contribute to open-source projects and community engagement.
  • Lead initiatives for continuous improvement in ML processes.
  • Assist in the development of training materials for users.

Requirements

Education
  • Bachelor's degree in Artificial Intelligence, Data Mining, or a related field
  • Master's degree is an advantage
Experience
  • 5+ years of experience in practical application of machine learning techniques
Technical Skills
  • Deep Learning
  • Data Visualization
Soft Skills
  • Creative problem solving
  • Adaptability
Certifications
  • Google Cloud Professional Data Engineer
Languages
  • English: Fluent

Advantageous

  • Experience with reinforcement learning: Understanding of reinforcement learning principles and techniques.
  • Participation in Kaggle competitions: Engagement in Kaggle competitions or other data science challenges.

Benefits

  • Full health, dental, and vision insurance
  • Generous retirement savings plan with matching contributions
  • Remote work options available
  • Employee training and mentorship programs

Company Culture

  • Diversity and Inclusion: We are committed to maintaining a diverse workforce and inclusive workplace.
  • Work-Life Balance: We believe in a healthy work-life balance, offering flexible working conditions.
Status: Closed