Overview
The Machine Learning Specialist will be integral to a dynamic ML team, focusing on developing and managing machine learning models for a prestigious global brand. The role involves taking ownership of the entire model lifecycle, from early exploratory work and validation to production deployment, ensuring that methodologies prioritize reproducibility and traceability. Collaboration with developer teams across the organization is essential, and the ideal candidate will have a solid ability to communicate complex results effectively to non-technical stakeholders.
Responsibilities
- Develop and manage machine learning models from exploratory analysis to production deployment.
- Implement clean experiment tracking and model versioning practices.
- Collaborate with cross-functional teams to integrate machine learning solutions.
- Apply strong validation methodologies, including experimental design and evaluation metrics.
- Visualize and communicate complex data insights to non-technical colleagues.
- Maintain good engineering practices, including version control and testing.
- Prototype innovative ML solutions to address business challenges as needed.
- Participate in knowledge sharing and mentoring within the ML team.
Requirements
- Strong proficiency in Python and experience with standard modelling and analysis libraries.
- Practical experience in building both supervised and unsupervised learning models.
- Solid understanding of validation disciplines, including experimentation and evaluation metrics.
- Experience in deploying models into production and ensuring clean handoffs with documentation.
- Ability to visualize data and explain technical concepts to non-technical audiences.
- Familiarity with version control and software testing best practices.
- Experience with Databricks, MLflow, or similar ML platforms is desirable.
- Knowledge of Azure and interest in the art market is a plus.