Responsibilities
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.
Requirements
Required:
- 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.
Others:
- 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.
Perks
- 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.
Application
You may apply for this opening via here. The deadline for this opening is 31 May, 2023.
