Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models in production, ensuring stable, reliable, and scalable performance.
For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
Build, test, deploy, and maintain production full-stack applications , working across React and TypeScript frontends, Python services using FastAPI or Django, SQL databases, APIs, authentication, and system integrations.
Designing, developing, and maintaining scalable data pipelines, BigQuery datasets, SQL transformations, and scheduled workflows that power Teleport's AI and Machine Learning products
Lead a team of young and bright MLOps Engineers in conducting research, design, and prototype MLOps practices, tools, and frameworks to expedite the machine learning lifecycle at MoneyLion.
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).