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Applied AI is a horizontal AI team at Uber partnering with product and platform teams across the company to deliver cutting-edge machine learning solutions for core business problems. The Computer Vision team in AppliedAI specializes in Generative AI, Foundation Model, and classical Computer Vision solutions, and the ML infrastructure needed to scale these systems in production.
Job Responsibility:
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
Requirements:
10+ years of industry experience in machine learning and 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 Python and scalable backend languages (e.g., Java, Go)
Excellent collaboration and communication skills with the ability to work across teams and functions
Nice to have:
MS in Computer Science, Machine Learning, or a related field
Hands-on experience integrating LLMs and ML models into products (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
What we offer:
Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp