Sr Software Engineer

Uber Uber · Consumer · San Francisco, CA +1 · Engineering

Uber is seeking a Sr Software Engineer to lead technical execution and drive architectural decisions for their Marketplace Segmentation team. This role involves collaborating with Product, Data Science, and other engineering teams to solve complex problems in real-time matching, dynamic pricing, and ML model integration, ultimately impacting critical products like UberX Priority and Wait & Save. The engineer will also mentor junior team members and contribute to the team's long-term technical vision.

What you'd actually do

  1. Lead the technical design and execution of complex features and medium-sized projects that significantly impact the team's products and strategic initiatives.
  2. Drive architectural decisions and system improvements within your area of ownership, ensuring scalability, reliability, and performance for critical marketplace services.
  3. Collaborate cross-functionally with Product, Data Science, Operations, and other engineering teams to define technical solutions, identify trade-offs (e.g., price vs. ETA), and align on roadmaps.
  4. Solve ambiguous and challenging technical problems related to real-time matching, dynamic pricing, ML model integration, or complex user experience flows.
  5. Champion engineering best practices, including testing, monitoring, and operational excellence, ensuring the health and stability of production systems.

Skills

Required

  • 5+ years of experience as a Software Engineer
  • proven track record of leading significant projects
  • Expertise in designing, building, and operating large-scale distributed systems in a production environment
  • Deep understanding of concurrency, fault tolerance, and performance optimization
  • Strong analytical and problem-solving skills
  • Excellent communication and collaboration skills
  • Experience mentoring junior engineers

Nice to have

  • Direct experience with marketplace platforms, demand/supply forecasting, or real-time optimization engines
  • Advanced degrees (Master's or Ph.D.) in Computer Science, Engineering, or a related field
  • Familiarity with causal inference and experimentation platforms (e.g., A/B testing, Synthetic Control)
  • Experience with Machine Learning (ML) system design and deployment

What the JD emphasized

  • ML model integration