Uber
AI

Sr Software Engineer - Matching ML Platform

Uber · Sunnyvale, CA · $202k

Actively hiring Posted 4 months ago

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 Sunnyvale, CA-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.

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Machine Learning Mlops Ai
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.