About the role
from listingStaff Software Engineer – ML Infra
About the Role & Team
Engineering at Uber means building for real-world impact under real-world constraints. As a Senior Software Engineer (ML Data & Backend) , you will architect mission-critical systems that power the foundation of trust across our global marketplace—from ensuring millions of earners are paid accurately and on time to scaling the simulation platforms that drive billions in pricing decisions. You will work on uniquely ambitious projects where performance, reliability, and scale cannot be separated.
The problems here are complex, the systems are massive, and the pace is fast. You’ll need to make smart decisions with imperfect information and own your work end-to-end: from the first design doc to debugging production issues when the stakes are highest. We are looking for technical powerhouses who think in systems, stay calm under pressure, and care about building things that actually work. If you’re energized by challenge and motivated by real-world impact—this is where you’ll grow.
What You’ll Do
System Design & Architecture: Design and build long-lasting engineering artifacts that reduce complexity and increase developer velocity across the organization. Foresee architectural problems or opportunities and work with leadership to address them before they impact the global marketplace.
Complex Problem Solving: Solve messy, high-impact problems at the intersection of low latency and high correctness, often without a clear starting point or obvious solution.
Technical Leadership: Lead organization-wide development and adoption of key frameworks while role-modeling coding best practices and high-quality design reviews.
Cross-Functional Collaboration: Partner closely with Product, Science, and Ops to translate ambiguous business requirements into production-ready technical roadmaps.
Mentorship & Culture: Mentor and guide other engineers, acting as a technical brand ambassador and raising the bar for engineering excellence across the organization.
Basic Qualifications
To be successful in this role, you should demonstrate hands-on experience across the following core layers of full-stack ML and backend systems:
9+ years of experience building developing ML models to solve business problem.
Bachelor’s degree in Computer Science, Computer Engineering, or related fields.
Familiar with modern AI/ML frameworks (e.g., PyTorch, Tensorflow).
Hands-on experience developing foundational models or Large Language Models (LLMs) for user facing applications, marketplace systems, recommendation engines, ad-tech platforms, or e-commerce/shopping infrastructures at scale.
Solid understanding of core machine learning algorithms, their applications, and the underlying systems/infrastructures required to train and serve them.
Proven track record in MLOps and ML Infrastructure (e.g., container orchestration via Kubernetes, data pipeline design, distributed workflow systems, and large-scale job scheduling).
Preferred Qualifications
Proven track record of owning distributed backend systems end-to-end in production environments with high availability requirements.
Strong fluency in system trade-offs between consistency, availability, latency, and operational cost.
Exceptional communication skills with the ability to articulate complex technical ideas to both technical and non-technical stakeholders.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.