We are looking for volunteers to design and create a MLOps system for managing current and future ML models. This project will entail using Databricks (Notebook + MLFlow + Backend) to build an architecture mainly in Python for standardizing the ML Model Development Lifecycle, from experimentation to deployment and maintenance. Potential to convert to a long-term volunteering position in our global leadership team with flexible commitment.
- Experience with one or more data science/ML libraries for Python, such as numpy, pandas, PyTorch, TensorFlow.
- Experience with working on a complete ML project involving most stages of the ML Model Development Lifecycle (feature engineering, model training, model tracking, service deployment, testing and operations). Preferred but not required:
- Experience with MySQL database and any artifact store knowledge.
- Basic understanding with containerising services, and experience in Docker.
- Experience with ML workflow/MLOps and related tools such as MLflow and Databricks.
- Passion in data analytics, algorithm design and machine learning in the context of real-life business needs.
- Desire to bring diverse perspectives, energy, knowledge and skills to the role.
- Learn/sharpen your skills in MLOps and broaden your project portfolio while knowing that your project will have a direct tangible impact on real-life businesses.
- Constant interactions with a growing global community of diverse, talented and passionate BfE members across the world.
You may apply for this opening via here. The deadline for this opening is 31 May, 2023.