Senior Localization Program Manager, Multilingual AI

Uber Uber · Consumer · Sunnyvale, CA · Engineering

This role focuses on building and scaling end-to-end localization workflows that integrate ML/LLM systems into Uber's global platform. It involves evaluating and operationalizing MT and LLM solutions, partnering with Engineering and MLOps to translate experimental AI into production-grade systems, and driving continuous improvement through quality frameworks.

What you'd actually do

  1. Design, build, and scale end-to-end localization workflows that integrate CMS, TMS, and ML/LLM systems to support Uber’s global movement.
  2. Evaluate and operationalize MT and LLM solutions across high and low-resource languages, leveraging GCP services like Vertex AI and BigQuery to balance performance with cost.
  3. Partner closely with Engineering and MLOps to translate experimental AI capabilities into production-grade systems, including model hosting, monitoring, and lifecycle management.
  4. Navigate complex trade-offs between translation quality, turnaround time, and infrastructure costs, providing data-driven recommendations to leadership.
  5. Lead cross-functional initiatives across global time zones, aligning Product, Data, and Vendor teams to ensure seamless execution and guardrail implementation.

Skills

Required

  • localization operations (CMS/TMS)
  • MT, LLM, or ML-driven language systems in a production setting
  • managing end-to-end technical programs
  • Google Cloud Platform (GCP) or similar cloud services, including Vertex AI, AutoML, or BigQuery

Nice to have

  • leading large-scale MT/LLM transformation programs
  • fine-tuning LLMs for multilingual use cases
  • implementing RAG pipelines for grounded translation
  • Python scripting or API integration
  • build data dashboards that track model performance, throughput, and cost-per-word metrics
  • navigating high-ambiguity environments and building frameworks for unique technical challenges

What the JD emphasized

  • production-grade infrastructure
  • production workflows
  • production setting
  • production-grade systems

Other signals

  • integrates Machine Translation and Large Language Models into the very fabric of our global platform
  • moving experimental capabilities into reliable production workflows
  • owning end-to-end impact and want to shape the future of global communication at scale