Machine Learning Engineer

Cape Town FULL TIME R41,667 - R62,500 / Month
(R500,000 - R750,000 / Year)

Job Description

We are seeking a talented Machine Learning Engineer to join our dynamic team in Cape Town. The ideal candidate will have a strong background in machine learning algorithms, model development, and data analysis. You will play a crucial role in developing AI-driven solutions to improve our products and services.

Responsibilities

  • Create and refine machine learning models for various use cases.
  • Engage with data engineering teams to ensure data quality and availability.
  • Participate in design reviews and code reviews to maintain best practices.
  • Research and implement new machine learning techniques to improve outcomes.
  • Develop and maintain comprehensive documentation of models and methodologies.
  • Engage with stakeholders to refine project requirements and deliver solutions.

Requirements

Education
  • Bachelor's degree in AI, Machine Learning, or related discipline
  • Master's degree is preferred
Experience
  • 3-5 years of relevant experience in machine learning or data science
Technical Skills
  • R
  • Big Data Technologies
  • Machine Learning Frameworks
Soft Skills
  • Creativity
  • Adaptability
Certifications
  • AWS Certified Machine Learning Specialty
  • Google Cloud Professional Data Engineer
Languages
  • English: Fluent

Advantageous

  • Experience with data engineering: Knowledge of data pipelines and ETL processes.
  • Interest in staying current with industry trends: A desire to explore the latest advancements in AI and machine learning.

Benefits

  • Comprehensive health and wellness benefits
  • Competitive salary with performance-related bonuses
  • Work from home flexibility
  • Support for ongoing education and training

Company Culture

  • Continuous Learning: We provide opportunities for team members to learn and grow through workshops and mentorship.
  • Supportive Leadership: Our leadership team is supportive and invested in the success of every employee.
  • Flexible Work Arrangements: We offer flexible work hours and environments to help our team achieve work-life balance.
Status: Closed