Machine Learning Engineer

PBT Group; Cape Town; On-site; ZAR 500,000 - 700,000; Full time

Job summary

A leading data solutions company in Cape Town is seeking a highly skilled Machine Learning Engineer. The role involves designing and deploying machine learning models while collaborating with data scientists and engineers. Strong proficiency in Python and hands-on experience with cloud platforms are critical. The ideal candidate has 3+ years of experience and a background in deploying ML models in real-world environments.

Qualifications

• 3+ years of experience in applied machine learning or AI solution development.
• Proven track record of delivering production‑ready ML models in real‑world environments.

Responsibilities

• Design, develop, and deploy machine learning models into production environments.
• Build and maintain end-to-end ML pipelines.
• Collaborate to move models from experimentation to production.
• Optimise model performance and ensure reliability.
• Implement MLOps best practices.
• Work with data engineers for data quality and governance.
• Research emerging AI/ML techniques.
• Document processes and provide technical guidance.

Skills

Strong proficiency in Python

Experience with MLflow, Kubeflow, SageMaker

Solid understanding of ETL/ELT processes

Hands‑on experience with AWS, Azure, or GCP

Strong SQL skills

Experience deploying ML models via APIs

Git, Jenkins, or GitHub Actions

Exposure to Deep Learning, NLP

Education

Bachelor’s or Master’s degree in a related field

Tools

Docker

Kubernetes

Airflow

Spark

Databricks

Job description

Machine Learning Engineer job vacancy in Cape Town.

PBT Group is seeking a highly skilled Machine Learning Engineer to design, build, and deploy scalable machine learning solutions across complex data environments.

The successful candidate will work closely with data scientists, data engineers, and business stakeholders to operationalise machine learning models, optimise data pipelines, and contribute to the continuous improvement of advanced analytics solutions.

This role requires a blend of strong data engineering expertise, applied machine learning knowledge, and cloud-based solution experience.

Duties and Responsibilities:

• Design, develop, and deploy machine learning models into production environments.
• Build and maintain end-to-end ML pipelines for data ingestion, transformation, feature engineering, model training, and inference.
• Collaborate with data scientists to move models from experimentation to production.
• Optimise model performance and ensure scalability, reliability, and monitoring of ML systems.
• Implement MLOps best practices, including CI/CD automation, version control, model tracking, and reproducibility.
• Work with data engineers to ensure robust data quality, governance, and accessibility.
• Research and experiment with emerging AI/ML techniques and tools to enhance capabilities.
• Document processes and provide technical guidance to cross-functional teams.

Technical Skills & Experience:

• Programming: Strong proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
• ML Lifecycle Management: Experience with MLflow, Kubeflow, SageMaker, or similar platforms.
• Data Pipelines: Solid understanding of ETL/ELT processes and tools such as Airflow, Spark, or Databricks.
• Cloud Platforms: Hands‑on experience with AWS, Azure, or GCP (data and AI services).
• Databases: Strong SQL skills and experience with both relational and NoSQL data stores.
• Model Deployment: Experience deploying ML models via APIs, containers (Docker, Kubernetes), or cloud endpoints.
• Version Control & CI/CD: Git, Jenkins, or GitHub Actions.
• Bonus: Exposure to Deep Learning, NLP, or Computer Vision frameworks.

Soft Skills:

• Strong problem‑solving and analytical skills.
• Excellent communication and collaboration with both technical and business stakeholders.
• Proactive and curious mindset, with the ability to learn and adapt quickly.
• Strong documentation and presentation abilities.

Minimum Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
• 3+ years of experience in applied machine learning or AI solution development.
• Proven track record of delivering production‑ready ML models in real‑world environments.