For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
Design, build and scale testing capabilities using AI agents – using GitHub Copilot Agent Mode on the GitHub Enterprise platform and the Microsoft AI Foundry stack – to automate testing tasks such as test case generation, test data creation, defect triage, and regression analysis.
Drive Real Impact: Lead an assigned project from inception to completion, applying your technical and analytical skills to solve a tangible business challenge (e.g., optimizing rider routing, scaling vendor acquisition).
Design, build, and maintain ML infrastructure and tooling to support the full ML lifecycle (data preparation, training, evaluation, deployment, monitoring, and retraining).
Design, build, and maintain end-to-end machine learning pipelines on Databricks, covering data preparation, feature engineering, model training, evaluation, and deployment.
Design, develop, and optimize generative AI models using deep learning techniques, such as NLP, transformers, GANs, and reinforcement learning, to address specific business needs like personalized customer interactions, automated document processing, and predictive analytics.
Drive Real Impact: Lead an assigned project from inception to completion, applying your technical and analytical skills to solve a tangible business challenge (e.g., optimizing rider routing, scaling vendor acquisition).