Machine Learning Engineer

Durban Full-time R50,000 - R60,000 / Month
(R600,000 - R720,000 / Year)

Job Description

We are seeking a talented Machine Learning Engineer to join our growing team in Durban. The successful candidate will be pivotal in developing cutting-edge machine learning models and driving impactful projects within the AI space. You will be part of a dynamic team focused on innovation and excellence, using data to solve real-world problems.

Responsibilities

  • Prototype and validate new machine learning approaches using relevant datasets.
  • Assist in deploying models within production environments and monitor their performance.
  • Collaborate with stakeholders to understand business requirements and identify opportunities for AI solutions.
  • Present findings and recommendations to technical and non-technical audiences.
  • Maintain best practices in coding and algorithm design.
  • Contribute to the overall technology strategy of the organization.

Requirements

Education
  • Bachelor's degree in Data Science or Machine Learning related field
  • A Master's degree would be advantageous
Experience
  • 3+ years of experience working with machine learning frameworks
Technical Skills
  • Scikit-learn
  • Keras
  • Data Visualization
Soft Skills
  • Critical Thinking
  • Time Management
Certifications
  • Microsoft Certified: Azure AI Engineer Associate
  • Certified Machine Learning Specialist
Languages
  • English: Fluent

Advantageous

  • Background in Software Engineering: Understanding of software engineering principles and practices.
  • Experience with Automated Machine Learning (AutoML): Knowledge of tools and techniques for automating the machine learning process.

Benefits

  • Full health benefits encompassing dental and vision care.
  • Annual bonuses tied to performance and project success.
  • Flexibility in work hours plus remote work arrangements.
  • Access to continuous learning and development programs.

Company Culture

  • Continuous Learning: We are committed to your professional growth, offering resources for continuous learning.
  • Work-Life Balance: We prioritize work-life balance and promote a healthy work environment.
  • Employee Recognition: We celebrate our employees’ achievements and contributions to the team's success.
Status: Closed