- Design and implement complex ML systems using classical machine learning, deep learning, and foundation models.
- Understand business objectives to develop models and relevant tracking metrics.
- Lead client communications, gather requirements, and manage project expectations.
- Wrangle, explore, and visualize data, addressing cleaning needs and distribution shifts.
- Analyze model errors and design strategies for performance improvement.
- Deploy, maintain, and upgrade ML models and pipelines.
- Collaborate with Data Engineering, DevOps, and Backend teams for seamless integration.
- Continuously optimize models for performance, scalability, and cost-effectiveness, particularly in AWS.
AWSPythonMachine Learning+5 more