Machine Learning Engineer – Retail AI

EXCITING FUTURE PROJECT COMING SOON!

EMPLOYMENT TYPE:

Contract (6-12 months with possible extension based on performance)

COMPANY:

Vito Solutions

CLIENT: 

A large retail chain

LOCATION:

Cape Town

WORKING MODEL:

Hybrid - Three days in-office, two days remote

JOB OVERVIEW:

We are looking for a Machine Learning Engineer to join our retail AI team. You will be responsible for developing, deploying, and scaling ML models that power customer personalization, inventory optimization, and operational efficiency across our retail network.

DESCRIPTION OF POSITION:

• Design, implement, and deploy scalable machine learning solutions for retail applications.
• Collaborate with Data Scientists to productionize predictive models.
• Develop data pipelines using SQL, Python, and cloud-native tools to feed ML models.
• Build and maintain ML infrastructure in cloud environments (GCP preferred; Azure/AWS acceptable).
• Optimize model performance, monitor for drift, and retrain as necessary.
• Implement MLOps best practices, including versioning, testing, and CI/CD for ML workflows.
• Collaborate with software engineers, product owners, and business stakeholders to integrate ML models into applications and systems.
• Ensure ML solutions are robust, maintainable, and secure.

KNOWLEDGE AND SKILLS:

• Proficient in SQL and relational databases.
• Solid understanding of machine learning algorithms, model evaluation, and data preprocessing.

QUALIFICATIONS REQUIRED:

Bachelors or Masters in Computer Science, Data Science, Machine Learning, or related field.

EXPERIENCE REQUIRED:

• 3–5+ years of experience as an ML Engineer or similar role.
• Strong programming experience in Python (including ML frameworks like TensorFlow, PyTorch, scikit-learn).
• Experience deploying ML models to cloud platforms (GCP preferred; Azure/AWS acceptable).
• Experience with MLOps practices and deployment pipelines.

ADVANTAGEOUS SKILLS:

• Experience with retail or e-commerce AI solutions (recommendations, demand forecasting, inventory optimization).
• Experience with containerization (Docker, Kubernetes).
• Knowledge of big data technologies like BigQuery, Spark, or Dataflow.
• Familiarity with data visualization tools (Tableau, Power BI, Looker).

**Please note: If you have not heard from us within 2 weeks, please consider your application unsuccessful.