About the Role
Uber is looking for a Software Engineer to join our Matching ML Platform team. This team sits at the core of Uber’s real-time marketplace, ensuring that riders and drivers are matched efficiently, fairly, and at scale.
Matching is one of Uber’s most complex and impactful engineering problems, requiring expertise in high-scale distributed systems, real-time decision-making, and machine learning infrastructure. As a Senior Engineer, you’ll play a key role in evolving our matching architecture, improving system efficiency, and enabling Uber’s next-generation ML-powered matching capabilities. This is an opportunity to work on one of Uber’s most business-critical domains with massive global impact.
Some of the problems you’ll be working on include:
- Building a highly scalable ml systems – handling millions of ride requests per second with ultra-low latency.
- Evolving the ML platform for matching – enabling real-time inference, model deployment, and experimentation at scale.
- Designing extensible architectures – creating a modular and flexible platform that allows new product innovations without complex rewrites.
What the Candidate Will Do:
- Build and scale a low-latency platform powering millions of real-time match decisions per second
- Identify opportunities to improve various ML system's performance and health
- Design modular systems that accelerate product innovation without rework
- Optimize for fairness, efficiency, and marketplace health at global scale
- Collaborate across product, infra, and ML teams to deliver business-critical impact
Basic Qualifications:
- 5+ years experience working on the full software life cycle including gathering requirements, project planning, solution design, coding/implementation, testing, rollout/deployment and best practices as an individual contributor.
- Experience with ML in production systems
- Experience coding using general purpose programming language (eg. C/C++, Java, Python, Go, C#)
- Fast and passionate learner. Strong collaboration, documentation and communication skills.
Preferred Qualifications:
- 3+ years of technical software engineering experience in one or more of the following areas:
- Experience building ML Models and ML infrastructure to support ML models
- Experience with distributed systems or microservice architectures.
- Experience with relational databases and distributed storage systems (MySQL, Cassandra).
- Experience with shipping efficient, reliable, crash-free code that reaches millions of users.
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 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. More details can be found at the following link https://jobs.uber.com/en/benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.