✨ About The Role
- The role involves designing, building, and enhancing batch and real-time inference services that support various ML use cases.
- The candidate will facilitate modelers by providing access to necessary infrastructure and tools for development, including MLOps.
- Developing prototypes and partnering with ML modelers to encourage the adoption of new tools and technologies is a key responsibility.
- The position is part of a new and growing team, allowing the candidate to significantly influence team culture.
- The role requires collaboration with cross-functional stakeholders to drive strategic roadmaps and priorities to completion.
âš¡ Requirements
- The ideal candidate will have over four years of combined experience in Machine Learning and Engineering, demonstrating full stack ML experience.
- A Bachelor's degree in a technical field such as computer science, data science, or applied mathematics is essential for this role.
- Familiarity with Linux/OS X command line and version control software like git is necessary, along with a solid understanding of software development principles.
- Experience collaborating with product, business, and engineering teams to prioritize and deploy ML models is crucial for success.
- The candidate should be proficient in the Python computing stack and have experience with cloud services like GCP or AWS for hosted models.