Machine Learning Engineer - Python

Description:

Responsibilities:

- Design and implement automated training and inference pipelines, including building a model registry system to track model artefacts, versioning, and lineage.

- Develop frameworks for on-demand model training and architect parallel processing systems for inference and event-driven architectures with multi-optimisation support.

- Design and develop sophisticated APIs that expose ML model capabilities.

- Build ETL pipelines specifically tailored for ML applications and develop preprocessing frameworks.

- Implement comprehensive monitoring solutions to identify system bottlenecks, optimise for enhanced scalability.

- Create infrastructure for offline and online experimentation.

- Build internal frameworks and tools that standardise ML workflows across the organisation.

- Stay current with developments in machine learning engineering and MLOps, evaluating and recommending new technologies and best practices.

- Contribute to technical decision-making and architecture discussions to shape the future of our ML infrastructure.

Requirements:

- Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent experience).

- 3+ years of experience in software engineering with a focus on ML systems.

- Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

- Experience building and maintaining production ML pipelines.

- Proficiency with containerization technologies (Docker, Kubernetes).

- Experience with cloud platforms (AWS, GCP, or Azure) and their ML services.

- Understanding of software engineering best practices, including version control, CI/CD, and testing.

- Experience with data processing frameworks.

- Strong problem-solving skills and ability to work independently on complex technical challenges.

- Excellent communication skills to collaborate with cross-functional teams