Machine Learning Engineer

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

Job Description

Looking for a Machine Learning Engineer ready to tackle exciting challenges in the AI field. This role will involve collaborating with data scientists and software engineers to build scalable machine learning systems. The ideal candidate will have strong programming skills and an analytical mindset to drive the development of advanced machine learning models.

Responsibilities

  • Design and refine machine learning frameworks for predictive modeling and data analysis.
  • Collaborate with software developers to implement machine learning solutions in production environments.
  • Monitor and troubleshoot machine learning models to ensure optimal performance.
  • Identify opportunities to automate processes using machine learning techniques.
  • Prepare reports and presentations on project outcomes for stakeholders.

Requirements

Education
  • Bachelor's degree in a scientific field or engineering
  • Master's degree in Artificial Intelligence or related is a plus
Experience
  • 3-5 years of experience as a Machine Learning Engineer or similar role.
Technical Skills
  • R
  • Deep Learning
  • APIs
Soft Skills
  • Problem-solving
  • Team Leadership
Certifications
  • Google Cloud Professional Machine Learning Engineer
  • AWS Certified Machine Learning
Languages
  • English: Fluent

Advantageous

  • Experience with reinforcement learning: Hands-on experience applying reinforcement learning techniques in projects.
  • Knowledge of data engineering: Experience with data pipelines and ETL processes.

Benefits

  • Attractive compensation scheme with annual bonuses.
  • Comprehensive health and wellness programs.
  • Work-life balance initiatives.
  • Career advancement opportunities within the company.

Company Culture

  • Continuous Learning: We prioritize lifelong learning and provide opportunities for professional growth.
  • Community Engagement: We are committed to positively impacting our local community through outreach programs and initiatives.
  • Work-Life Balance: We support a healthy work-life balance and flexible working arrangements.
Status: Closed