Machine Learning Engineer

Job Description

We are on the lookout for a talented Machine Learning Engineer to join our dynamic team in Johannesburg. As a part of our AI department, you will be instrumental in developing and implementing machine learning models that solve complex problems and contribute to our innovative projects. The ideal candidate will have a strong grounding in machine learning methodologies, programming skills, and a passion for curating datasets to create efficient algorithms.

Responsibilities

• Design and build machine learning applications to automate data processing tasks.
• Work closely with the team to understand project requirements and translate them into ML solutions.
• Test and validate models to ensure robustness, accuracy, and scalability.
• Prepare reports and presentations on findings and recommendations based on model outputs.
• Participate in team meetings to share insights and discuss potential optimizations.

Requirements

Education

• Bachelor's degree in a quantitative field
• Master's degree in Data Science or related field is preferred

Experience

• 3+ years of experience in ML technologies and projects

Technical Skills

• Python
• Keras
• R

Soft Skills

• Teamwork
• Problem-solving

Certifications

• Machine Learning Certification from a recognised institution
• AI Specialization Certification

Languages

• English: Fluent

Advantageous

• Experience with deploying models in production environments: Expertise in bringing machine learning models to production for application use.
• Familiarity with MLOps practices: Understanding of operationalizing machine learning in production.

Benefits

• Comprehensive health and wellness benefits
• Flexible working arrangements
• On-site gym access and wellness programs
• Organized team-building activities

Company Culture

• Diversity and Inclusion: We celebrate diversity and are committed to building an inclusive team.
• Work-Life Balance: We prioritize work-life balance, offering flexible schedules to support family and personal life.
• Community Engagement: Actively participate in community initiatives and programmes focused on social responsibility.