Responsibilities
- Design and implement machine learning models that power core artificial intelligence functions including natural language understanding, information retrieval, ranking, logical reasoning, conversation systems, and code generation.
- Develop and apply cutting-edge machine learning techniques such as Transformer architectures, reinforcement learning, ensemble methods, and agent-based models to enhance system performance.
- Lead efforts in processing and analyzing large-scale datasets with varying structures, including structured, semi-structured, and unstructured data, to guide model development.
- Own the full machine learning lifecycle from defining problems and exploring data to engineering features, training models, validating results, and deploying solutions.
- Establish A/B testing frameworks and statistical validation methods to measure model impact and build automated testing pipelines ensuring reliability and accuracy.
- Explain technical aspects and business value of machine learning systems clearly to both engineering teams and non-technical partners to drive alignment and adoption.
