Apply statistical modeling and deep learning expertise as a Senior Machine Learning Engineer on a fully remote, asynchronous team. Build intelligent systems from large-scale datasets.

This senior role develops, implements, and deploys advanced machine learning models. You will build pipelines, support production systems, and contribute to ML infrastructure architecture. Collaboration spans data scientists, software engineers, and product managers while MLOps practices support continuous delivery and monitoring.

Key Responsibilities:

- Design state-of-the-art machine learning models and algorithms
- Build pipelines for preprocessing, feature engineering, training, and evaluation
- Deploy production models for scalability, reliability, and performance
- Implement MLOps practices for integration,



delivery, and monitoring
- Mentor junior engineers and share team knowledge

Requirements:

- Six years of professional machine learning engineering experience
- Master’s or Ph.D. in a quantitative related field
- Strong Python and TensorFlow, PyTorch, scikit-learn, or Keras proficiency
- Experience with MLflow, Kubeflow, Docker, or Kubernetes
- Solid analytical, communication, and independent project-management abilities

Use statistical modeling, deep learning, Python, and MLOps to deliver responsible machine learning systems remotely.

📌 Senior Machine Learning Engineer (Kimberley)
🏢 Placements24
📍 Kimberley