Staff Machine Learning Engineer - Applied AI

About The Role

Applied AI at Uber builds intelligent systems that power next-generation product experiences for riders, drivers, merchants, and couriers. As a Staff AI Engineer , you will work end-to-end across product development - from data pipelines and backend integration to real-world AI deployment - building scalable, intelligent, and user-centric experiences.

You will leverage large language models (LLMs) and multimodal AI systems to create production-ready applications, integrating APIs from OpenAI, Anthropic Claude, Google Gemini, and other emerging models. You'll also pioneer LLM-based evaluation methods , including LLM-as-a-judge frameworks that automate assessment of model outputs and enhance product quality.

This is an opportunity for a technical leader who thrives at the intersection of AI, engineering, and product , driving innovation and measurable impact across Uber's ecosystem.

What You'll Do

• Build end-to-end AI products - from prototype to scalable production deployment - integrating LLMs and multimodal AI into Uber's consumer, earner, and enterprise experiences.
• Implement automated evaluation systems that use LLM-as-a-judge techniques to benchmark model quality, ensure consistency, and accelerate experimentation.
• Design and implement services and APIs that connect to leading AI models (e.g., OpenAI, Claude, Gemini, Mistral), ensuring reliability, latency efficiency, and cost optimization.
• Develop pipelines for training, fine-tuning, and evaluating AI models; manage data ingestion, cleaning, labeling, and experimentation workflows.
• Perform data science and analytics work to understand performance metrics, user behavior, and model outcomes, ensuring responsible and measurable AI impact.
• Collaborate across disciplines (engineering, product, design, and data science) to define user problems and translate them into AI-powered solutions.
• Champion best practices in AI model evaluation, safety, observability, and responsible use of generative AI.
• Mentor engineers and data scientists , fostering a culture of technical excellence and cross-functional learning.
  
  

Basic Qualifications:

• 10+ years of experience in software engineering, data science, or machine learning, including a track record of shipping production AI systems.
• Deep understanding of large language models , including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG).
• Strong backend engineering skills in Python, Go, or Java , with experience integrating third-party APIs.
• Hands-on experience building data pipelines and ETL systems (e.g., Spark, Airflow, Flink, or similar).
• Ability to analyze data, run experiments, and derive insights for model and product improvement.
• Familiarity with cloud environments (AWS, GCP, or similar) and ML frameworks (PyTorch, TensorFlow, or JAX).
• Excellent communication and collaboration skills across technical and non-technical teams.
  
  

Preferred Qualifications:

• Master's or Ph.D. in Computer Science, Data Science, or related field.
• Experience integrating foundation model APIs (OpenAI, Claude, Gemini, Cohere, etc.) into production-grade systems.
• Proven ability to architect AI-powered backend services , optimizing for scalability, latency, and cost efficiency.
• Background in LLM evaluation systems or AI agent orchestration frameworks (LangChain, Semantic Kernel, etc.).
• Demonstrated success leading cross-functional projects that deliver measurable user or business impact.
• Familiarity with multimodal AI (text, speech, and image models) and data-centric development workflows .