Your responsibilities
- Research: Follow cutting-edge research in human avatars and discuss recent advances with your peers
- Experimentation: Reimplement research papers and experiment with new open-source tools to build a fast, robust, and hyper-realistic audio-driven avatar generation pipeline
- Productionalization: Turn PoCs into scalable and robust ML components that you deploy to production and scale to millions of users
- ML Monitoring: Own your ML components end-to-end, monitor and understand their real-life performance, and devise usage-driven suggestions for improvement
- Code Quality: Maintain high code quality through regular code reviews, pair programming, and writing unit and integration tests.
- Collaboration: Collaborate with other MLEs, research scientists, and other engineers on creating and deploying a robust and scalable end-to-end avatar streaming pipeline consisting of multiple components that work together seamlessly