Machine Learning Engineer - Applied AI

Uber's Applied AI team is at the forefront of leveraging cutting-edge Artificial Intelligence and Machine Learning technologies to enhance the Uber experience for millions of users globally. The team collaborates with product teams across Uber to deliver innovative AI solutions for core business problems, working closely with engineering, product, and data science teams.

The Applied AI team is building Natural Language and Computer Vision capabilities for multimodal document understanding. They are seeking a strong Machine Learning Engineer to join their team in Seattle.

Responsibilities:

• Train, evaluate, and deploy Machine Learning models
• Develop distributed pipelines to analyze and process large datasets
• Collaborate with cross-functional teams to understand business problems and deliver end-to-end Machine Learning solutions
• Stay current with the latest advancements in AI/ML and integrate new technologies into the team's work

Basic Qualifications:

• Masters or equivalent in Computer Science, Engineering, Mathematics, or related field
• 2 years of Software Engineering work experience
• Experience in programming with Python
• Experience with modern Machine Learning methods, such as Deep Learning
• Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn
• Experience in the development, training, productionization, and monitoring of ML solutions at scale

Preferred Qualifications:

• 4 years of Software Engineering work experience
• Experience in Natural Language Processing (NLP) and Computer Vision
• Experience in modern generative AI, such as transformer architectures, diffusion models, and prompting
• Publications or contributions to AI/ML research in top conferences or journals

Uber offers a competitive salary range, bonus program, potential equity awards, and various benefits. They are committed to equal opportunity employment and consider qualified applicants regardless of background or criminal history, consistent with legal requirements.