Machine Learning Engineer

Cape Town Full-time R50,000 - R66,700 / Month
(R600,000 - R800,000 / Year)

Job Description

We are seeking an enthusiastic Machine Learning Engineer to join our vibrant team in Cape Town. The ideal candidate will possess a strong foundation in machine learning algorithms, data processing, and model optimization. Your role will involve designing and implementing cutting-edge machine learning models and collaborating with cross-functional teams to enhance our AI-driven projects.

Responsibilities

  • Create prototypes and proof of concepts for new machine learning applications.
  • Collaborate in an agile environment with data scientists and engineers.
  • Perform regular assessments of model accuracy and retrain as necessary.
  • Write reusable, testable code for machine learning applications.
  • Develop deployment strategies for machine learning models.

Requirements

Education
  • Bachelor's degree in Computer Science or Statistics
  • Master's degree in Data Science is an advantage
Experience
  • 4+ years of experience in machine learning and data analytics
Technical Skills
  • R Programming
  • Deep Learning
Soft Skills
  • Communication
  • Problem Solving
Certifications
  • Google Professional Data Engineer
  • Microsoft Certified: Azure Data Scientist Associate
Languages
  • English: Fluent

Advantageous

  • Public Speaking Skills: Ability to present complex information clearly to technical and non-technical audiences.
  • Knowledge of Natural Language Processing (NLP): Experience with NLP techniques and applications.

Benefits

  • Retirement savings plan with company contribution
  • Career development programs
  • Inclusive company culture promoting diversity
  • Monthly team-building activities

Company Culture

  • Diversity and Inclusion: We embrace diversity and are dedicated to creating an inclusive workplace for all.
  • Work-Life Balance: We prioritize work-life balance, offering flexible work schedules and remote options.
  • Community Engagement: We support community initiatives and encourage employee participation in volunteering.
Status: Closed