Machine Learning Engineer

Durban FULL TIME R41,667 - R70,833 / Month
(R500,000 - R850,000 / Year)

Job Description

We are seeking a skilled Machine Learning Engineer to join our dynamic team in Durban. The ideal candidate will possess strong expertise in machine learning algorithms and be passionate about developing cutting-edge AI solutions that solve real-world problems. The role involves working closely with cross-functional teams to design, develop, and implement machine learning models while ensuring their efficiency and scalability.

Responsibilities

  • Implement machine learning models into existing software applications.
  • Evaluate model accuracy and performance using appropriate metrics.
  • Collaborate with data engineers to ensure data quality and availability.
  • Assist in developing best practices for machine learning deployment.
  • Provide training and support to team members on machine learning techniques.
  • Contribute to the continuous improvement of machine learning processes.

Requirements

Education
  • Bachelor's degree in Mathematics, Statistics, or related field
  • Master's degree in a related field is a plus
Experience
  • 4+ years of experience in machine learning or data analysis
Technical Skills
  • R Programming
  • Scikit-learn
Soft Skills
  • Effective Communication
  • Adaptability
Certifications
  • Google Professional Machine Learning Engineer
Languages
  • English: Fluent

Advantageous

  • Knowledge of reinforcement learning: Experience in developing reinforcement learning algorithms.
  • Experience in model optimization techniques: Familiarity with tuning hyperparameters for better performance.

Benefits

  • Comprehensive medical aid coverage
  • Performance bonuses
  • Remote work flexibility after initial training
  • Paid time off and leave entitlements

Company Culture

  • Diversity and Inclusion: We respect and value diverse backgrounds and perspectives, creating an inclusive culture.
  • Employee Empowerment: We empower employees to take ownership of their work and contribute to decision-making.
  • Work-Life Balance: We promote a healthy work-life balance to ensure employee well-being.
Status: Closed