Jobs
About the Role
Uber's Road Safety and Insurance Engineering teams sit at the intersection of real-world mobility, large-scale data systems, and safety-critical decision making. Our systems process petabytes of telematics, sensor, and behavioral data that help detecting crashes, assess driving riskand ultimately make every trip safer.
Every Uber trip, across ridesharing, delivery, and emerging mobility products, is made safer by the systems this role helps build. With #Stand For Safety as a company-wide priority, this is a rare opportunity to shape backend platforms that operate at massive scale and have real-world impact.
We are looking for a Senior Staff Backend Engineer to provide technical leadership across Road Safety and Insurance engineering teams**, leading complex, multi-team initiatives that span real-time data ingestion, signal processing, machine learning-powered risk assessment, and highly reliable backend platforms.**
What You'll Do:
As a Senior Staff Engineer, you will operate as a technical leader across teams**, not just within a single codebase.**
You will:
- Lead large, cross-team technical initiatives **collaborating with multiple platform teams, from early design through production rollout.**2. Builds strategic relationships **with internal stakeholders (e.g. engineering leaders, product managers, designers, operations representatives), partner teams and external partners to deliver on organizational goals.3. Design and evolve backend systems that ingest, process, and analyze high-volume sensor and telematics data(e.g., GPS, accelerometer, gyroscope, vehicle signals and user feedbacks).**4. Partner closely with machine learning and data science teams **to productionize ML and signal-processing models for crash detection, driving behavior detection etc.5. Drive architectural decisions for low-latency streaming pipelines, distributed services, and offline/online data processing systems.6. Anticipate and address scalability, reliability, and data quality challenges1-2 years ahead, influencing platform direction proactively.**7. Set and role-model engineering best practices **around system design, code quality, observability, incident response, and on-call excellence.**8. Mentor Senior engineers and Staff Engineers, raising the technical bar across the org.
- Represent the org in company-wide technical discussions**, design reviews, and architecture forums.**
Basic Qualifications:
- BS or equivalent in Computer Science, Engineering, Mathematics, or a related field.
- Proven experience designing and building large-scale distributed systems **serving millions of users.**3. Strong computer science fundamentals: data structures, algorithms, system design, and performance optimization.
- Demonstrated ability to lead complex projects across multiple teams or organizations**.**
Preferred Qualifications:
- 10+ years of professional software engineering experience**, with significant backend depth.2. Experience working with telematics, sensor data, time-series data, or signal processing systems.3. Hands-on experience with streaming and real-time data pipelines(e.g., Kafka-like systems, stream processing frameworks).4. Exposure to machine learning systems in production, including model integration, feature pipelines, or ML-powered decision systems.**5. Strong background in scalability engineering, data consistency, and system observability.
- Track record of influencing architecture and technical direction across multiple teams.
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For San Francisco, CA-based roles: The base salary range for this role is USD**$267,000 per year**
-
USD**$297,000 per year**.
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For Sunnyvale, CA-based roles: The base salary range for this role is USD**$267,000 per year**
-
USD**$297,000 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.
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total / year
Base
$161,000
Stock
-
Bonus
-
$203,580
$209,300
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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