Staff Software Engineer - Traffic Machine Learning

About the Role

Engineering at Uber means building for real-world impact under real-world constraints. The Traffic team owns the real-time heartbeat of our platform—processing road data, incidents, closures, and weather that dictate how every Uber trip is routed and priced. This isn’t a place for theoretical exercises; you will be building the systems that millions of people rely on to get where they’re going in the real world.

The work is high-stakes and technically complex. You will be dealing with massive scale and the inherent messiness of real-world data, where performance and safety are inseparable. We need someone who thinks in systems, stays calm when production latency spikes, and has the grit to navigate technical debt while building for the future. If you thrive in high-autonomy environments and want to own the technical vision for one of Uber’s most critical domains, this is where you’ll grow. If you prefer a predictable playbook or a slow pace, this likely isn't the right fit.

What You’ll Do

• Design, build, and maintain data pipelines that process real-time road data at a global scale, where every millisecond of latency impacts millions of ETAs.
• Lead technically complex initiatives, such as re-architecting our incident and closure detection systems to improve accuracy and reaction time.
• Solve messy, high-impact problems—like optimizing the interface between traffic and routing—often without a clear starting point or obvious solution.
• Navigate the trade-offs between short-term tactical fixes and long-term architectural stability while keeping our Maps ecosystem running smoothly.
• Own your work end-to-end, from drafting the multi-year technical vision for traffic domains to debugging production issues when the stakes are high.
• Collaborate cross-functionally with Data Scientists, Product Managers, and Engineering peers to translate complex business needs into robust, scalable software.
• Champion engineering best practices like code health and design clarity, even when the pace is fast and priorities shift.
• Mentor and unblock other ICs on the team, raising the bar for technical excellence through thoughtful design reviews and leadership by example.

Basic Qualifications

• Proficiency in building and maintaining high-scale data pipelines using systems like Flink or Spark.
• Experience with data analysis techniques and the ability to reason about system performance, headroom, and data quality.
• Experience leading major technical initiatives from inception through to production and maintenance.
• Ability to work across multiple technical domains in parallel, zooming into code-level details and out to system-level strategy.
• Ability to lead through others, driving results from more junior engineers on the team.

Preferred Qualifications

• Experience with machine learning systems and an understanding of the end-to-end ML lifecycle.
• Domain expertise in traffic modeling, ETA prediction, route optimization, or other areas heavy on real-time geospatial data.
• A proactive, entrepreneurial mindset with a track record of identifying impactful projects and driving them to success.
• Systems thinking approach to reducing latency and improving reliability in distributed environments.

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 fuelds progress. What moves us, moves the world - let’s move it forward, together.

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.

*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.