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Uber

Staff Software Engineer - Engineer

Posted 8 Days Ago
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In-Office
Toronto, ON, CAN
Senior level
In-Office
Toronto, ON, CAN
Senior level
Lead architecture and delivery of scalable Maps Search systems, including backend services, retrieval, autocomplete, recommendations, data pipelines, and ML serving infrastructure. Improve latency, reliability, relevance, observability, and operational health for high-throughput services. Set technical direction across teams, make system-level tradeoffs, mentor engineers, and collaborate with product, machine learning, science, mobile, and infrastructure partners.
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About the role and team 

Uber Maps Search helps people find the places and destinations they need across Uber experiences. The multi-disciplinary team builds the backend systems, deep learning models & user experience components behind location search - from understanding a query and retrieving relevant places to serving useful results with the speed and reliability people expect. Because location search is the 1-step of any Go-Get experience at Uber, the team's contributions meaningfully influence Uber’s business performance, and the team’s work is highly visible to the executive leadership team.

As a Staff Software Engineer, you’ll set technical direction for important, multi-quarter initiatives and help evolve the services and data foundations that power search. You’ll partner closely with machine learning, science, mobile, and other engineering teams to turn customer and business needs into scalable systems. This is a hands-on technical leadership role: you’ll shape architecture, guide delivery across teams, and raise the quality and reliability of the platform.

What you’ll do 

  • Lead the architecture and end-to-end delivery of high-impact Maps Search projects, from problem definition and technical strategy through launch and ongoing operation.
  • Design, build, and evolve scalable backend services for location search, including query handling, autocomplete, retrieval, result aggregation, and recommendation-serving workflows.
  • Improve the latency, availability, relevance, and operational health of high-throughput search systems, using data and production signals to identify and address bottlenecks.
  • Build and maintain dependable data pipelines and serving infrastructure that bring search and machine-learning capabilities into production.
  • Make thoughtful system-level tradeoffs across service boundaries, data freshness, quality, cost, and reliability; communicate decisions and establish durable technical direction.
  • Partner with product, machine learning, science, mobile, and infrastructure teams to define goals, align dependencies, and deliver cohesive customer experiences.
  • Raise the technical bar through design and code reviews, practical engineering standards, and hands-on mentorship of engineers across the organization.
  • Strengthen operational excellence through observability, incident follow-up, capacity planning, and improvements to on-call health.

 Basic Qualifications 

  • 8+ years of professional software engineering experience building and operating backend services or distributed systems.
  • Strong programming skills in at least one backend language, such as Java, Go, C++, or Python.
  • Demonstrated technical leadership on complex, cross-team projects, including setting architecture and driving delivery from conception to production.
  • Experience designing systems for scale, reliability, and low latency, and diagnosing issues in production environments.
  • Strong fundamentals in data structures, algorithms, API design, and system design.
  • Ability to communicate technical decisions clearly and work effectively with engineering and non-engineering partners.
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

 Preferred Qualifications 

  • Experience building search, information retrieval, ranking, recommendation, or geospatial products.
  • Experience with high-QPS, latency-sensitive consumer-facing systems and distributed service architectures.
  • Experience building data pipelines, indexes, or online serving systems for machine-learning-powered products.
  • Familiarity with search relevance, query understanding, personalization, semantic search, or multi-source retrieval.
  • Experience improving production reliability, observability, and operational practices for critical services.
  • A track record of influencing technical direction across teams and mentoring senior engineers.
  • Graduate degree in Computer Science or a related technical field.
Responsibilities

For Canada-based roles: The base salary range for this role is CAD $197,000 per year - CAD $219,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits.

About Us

Ready to Ride?

This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

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.

Uber Toronto, Ontario, CAN Office

1457 McCowan Rd Suite 217, Toronto, ON, Canada, M1S 5K7

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