The Role

We're looking for a Machine Learning Engineer who thrives at the intersection of data science and production systems. You'll design and deploy scalable ML pipelines, optimize model performance, and automate end-to-end workflows ensuring seamless integration between models, data, and business applications.

Snapshot

• Location: Cape Town, Johannesburg, Remote

• Employment Type: Full-time, Contract

Key Responsibilities

• Build and maintain production-grade ML pipelines for deployment.

• Design automated workflows for model retraining, monitoring, and version control.
• Optimize inference speed, scalability, and cost-efficiency across cloud environments.
• Collaborate with data engineers and data scientists for seamless model integration.

• Work with containerized ML infrastructure (Docker, Kubernetes, MLflow).

• Monitor model drift, data quality, and performance metrics in production.

• Maintain high standards of reliability, documentation, and reproducibility.

Skills & Experience

• 5 - 8+ years of experience in Machine Learning or AI engineering.

• Proficient in Python and ML frameworks: TensorFlow, PyTorch, scikit-learn.
• Hands-on experience deploying models using Docker, Kubernetes, MLflow.

• Strong understanding of MLOps principles and CI/CD pipelines for ML.

• Familiar with AWS SageMaker, Azure ML, or GCP Vertex AI.

Nice to Have

• Experience with distributed training and GPU optimization.

• Knowledge of orchestration tools: Airflow, Kubeflow, or Prefect.

• Familiarity with real-time data streaming (Kafka, Spark Streaming).

Salary

• R60k/month - R150k/month

Culture & Benefits

• Collaborative, forward-thinking engineering culture.

• Emphasis on technical excellence, ownership, and system sustainability.

• Autonomy in decision-making and mentorship opportunities.

• Chance to shape foundational ML infrastructure for enterprise-scale systems.

• Discretionary performance-based bonus.