Machine Learning Engineer

Cape Town FULL TIME R45,800 - R60,000 / Month
(R550,000 - R720,000 / Year)

Job Description

We are seeking a highly skilled Machine Learning Engineer to join our innovative team in Cape Town. As a key player, you will design, implement, and optimize machine learning algorithms, enabling our organization to leverage advanced data analytics for strategic advantages.

Responsibilities

  • Design, build and evaluate machine learning applications and systems.
  • Work closely with cross-functional teams to define and deliver effective solutions.
  • Optimize and fine-tune existing machine learning models for improved results.
  • Analyze model performance and extract meaningful insights from data.
  • Participate in peer reviews to ensure quality and best practices in ML engineering.
  • Develop training and validation workflows for machine learning models.

Requirements

Education
  • Bachelor's degree in a quantitative field
  • Master's degree or PhD is preferred
Experience
  • 5+ years of experience in machine learning or AI-related roles
Technical Skills
  • Deep Learning
  • Natural Language Processing
Soft Skills
  • Adaptability
  • Communication
Certifications
  • Deep Learning Specialization
  • Google Professional Data Engineer
Languages
  • English: Fluent

Advantageous

  • Familiarity with big data technologies like Hadoop or Spark: Experience in processing and analyzing big data for machine learning applications.
  • Experience with containerization tools like Docker: Hands-on experience in using Docker for deploying machine learning applications.

Benefits

  • Attractive salary with annual performance incentives
  • Comprehensive health and wellness benefits
  • Flexible schedules and hybrid work arrangements
  • Opportunities for professional growth and upskilling

Company Culture

  • Diversity and Inclusion: We value diversity and are committed to creating an inclusive workplace where everyone feels welcome.
  • Work-Life Balance: We believe in maintaining a healthy work-life balance for our employees.
  • Community Engagement: We actively engage in community initiatives and promote social responsibility.
Status: Closed