Staff Software Engineer - AI Platform (Michelangelo)

About the position

Partners with stakeholders and leads team efforts to build and maintain Machine Learning backend services and solutions to support user-facing products, downstream services, or infrastructure tools and platforms used across Uber.

Responsibilities

• Design and build tools to empower production teams to innovate and productionize state-of-the-art deep learning models at Uber.
• Develop and maintain scalable, end-to-end deep learning training systems and frameworks.
• Ensure distributed training tools are reliable, efficient, flexible to use for new production use cases.
• Collaborate with cross-functional teams including machine learning engineers, backend engineers, data scientists, and data engineers to deliver robust ML solutions for Uber.

Requirements

• Master in relevant fields (CS, EE, Math, Stats, etc.) AND 6-years full-time Software Engineering work experience in deep learning.
• Proficiency in Python and PyTorch.
• Expertise in designing, debugging, and optimizing distributed deep learning systems.
• Working experience of distributed training in PyTorch at Scale (e.g., data parallelism, model parallelism).
• Strong ability to translate complex DL requirements and problems into scalable solutions.

Nice-to-haves

• Expertise in distributed training frameworks such as DDP, DeepSpeed, FSDP, or TorchRec.
• Familiarity with C++, Go or CUDA programming.
• Expertise in optimizing GPU/TPU training performance and data loading efficiency.
• Familiarity with large-scale distributed infrastructure tools like Ray, OpenAI Triton, PyTorch Lightning.
• Built and deployed end-to-end machine learning systems in production.
• Experience training large models (10B+ parameters), such as large recommendation systems or large language models (LLMs).
• PhD in relevant fields (CS, EE, Math, Stats, etc.).

Benefits

• Eligible to participate in Uber's bonus program.
• May be offered an equity award & other types of compensation.
• Eligible for various benefits.