Uber Staff ML Engineer - Applied AI 

United States, West Virginia 

741753461

What You’ll Do

• Design and implement ML-driven systems that power core Uber experiences, with a focus on scalability, reliability, and performance.
• Lead the technical execution of key projects involving classical ML, deep learning, and generative AI technologies (e.g., LLMs, multimodal models).
• Collaborate closely with product, data science, and infrastructure teams to develop AI solutions from ideation through production deployment.
• Contribute to and influence the technical direction for Applied AI, particularly around system design, model architecture, and infrastructure decisions.
• Champion engineering best practices in ML development — including experimentation workflows, model versioning, evaluation, monitoring, and responsible AI.
• Provide mentorship to engineers on the team and across partner orgs to help raise the technical bar.

Basic Qualifications

• 10+ years of industry experience in machine learning or software engineering, with a proven record of delivering ML solutions to production.
• Strong knowledge of machine learning, deep learning, and exposure to generative AI techniques (e.g., transformers, LLMs, diffusion).
• Experience designing and scaling ML systems or platforms, including training pipelines, serving infrastructure, and model lifecycle tooling.
• Fluency in ML frameworks (e.g., PyTorch, TensorFlow, JAX) and development in Python and/or scalable backend languages (e.g., Java, Go).
• Excellent collaboration and communication skills with the ability to work across teams and functions.

Preferred Qualifications

• PhD in Computer Science, Machine Learning, or a related field.
• Hands-on experience integrating LLMs or generative models into product experiences (e.g., summarization, personalization, automation).
• Familiarity with MLOps, experimentation frameworks, or ML observability tools.
• Track record of technical leadership in multi-disciplinary projects involving engineering, data science, and product.

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .