✨ About The Role
- The role involves building data pipelines to collect high-quality training and evaluation data for AI model development.
- The candidate will be responsible for creating annotation pipelines that utilize both human input and AI models.
- Close collaboration with AI product engineers will be necessary to define requirements for AI features.
- The position requires working with AI researchers to identify failure cases and improve datasets and evaluation metrics.
- The candidate will also work with AI infrastructure engineers to develop the necessary infrastructure for AI model development and inference.
- There will be opportunities to explore the boundaries of current technology and experiment with novel ideas.
âš¡ Requirements
- The ideal candidate will have expertise in building infrastructure for AI/ML model development in an industry setting.
- A strong background in software development, particularly in Python, is essential for success in this role.
- Experience collaborating closely with AI researchers on applied AI projects is crucial to build high-quality models efficiently.
- The candidate should have a proven track record of improving datasets and evaluation metrics for applied machine learning projects.
- Strong problem-solving skills and the ability to evaluate alternative solutions and trade-offs are necessary for this position.
- Excellent communication skills are required to work effectively across functions and drive solutions.