Machine Learning Engineer

Cape Town FULL TIME R50,000 - R66,667 / Month
(R600,000 - R800,000 / Year)

Job Description

We are looking for a Machine Learning Engineer to join our vibrant team in Cape Town. This role involves developing and implementing machine learning models aimed at solving complex business challenges. If you have a passion for AI and a knack for identifying data-driven insights, we want to hear from you!

Responsibilities

  • Create predictive models and machine learning algorithms tailored to business needs.
  • Collaborate in agile teams to design and refine product features.
  • Evaluate and improve existing data models for accuracy and efficiency.
  • Present findings and recommendations to stakeholders and team members.
  • Contribute to a culture of innovation and experimentation within the team.
  • Lead technical discussions and mentor junior team members.

Requirements

Education
  • Bachelor's degree in Data Science, Computer Science, or a related field
  • Master's degree in a related field is preferred
Experience
  • 4+ years of experience in machine learning and predictive modeling
Technical Skills
  • R
  • Deep Learning
Soft Skills
  • Team collaboration
  • Adaptability
Certifications
  • AWS Certified Machine Learning
  • Google AI Engineer
Languages
  • English: Fluent

Advantageous

  • Familiarity with Big Data technologies: Experience with tools like Hadoop or Spark for large-scale data processing.
  • Background in software engineering principles: Understanding of software development life cycles and methodologies.

Benefits

  • Full medical coverage for employees and dependents
  • Pension fund with company match
  • Work-from-home options and flexible schedules
  • Support for ongoing training and certifications
  • Regular company retreats and social events

Company Culture

  • Data-Driven Approach: Our decisions are informed by data insights, leading to better outcomes for our clients.
  • Inclusiveness: We strive for diversity and accept contributions from all backgrounds in our team.
  • Work-Life Balance: We believe in maintaining a healthy work-life balance for all employees.
Status: Closed