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Sr. Staff Engineer (Conversational/Voice AI)

Uber

Sr. Staff Engineer (Conversational/Voice AI)

Uber

San Francisco, CA; Sunnyvale, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$267,000 - $267,000

Benefits & Perks

Competitive salary and equity package

Comprehensive health, dental, and vision insurance

Generous paid time off and holidays

Team events and activities

Equity

Healthcare

Required Skills

Python

JavaScript

TypeScript

About the Role

Uber's Customer Obsession team builds the platform and AI that powers world-class support across mobile, web, and voice at global scale. We are now hiring a Senior Staff Engineer to architect, productionize, and scale an autonomous support agent that resolves customer issues end-to-end. Experience with voice agents and agentic architectures is a major plus. You'll push the state of the art in GenAI for customer service-LLM orchestration, evaluation, safety guardrails, multilingual support, and real-time voice-while holding a very high bar for reliability and cost efficiency. We are still at an early stage and value candidates with bias for action who get creative with GenAI tools to accelerate execution and experimentation.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

  1. Own the end-to-end agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on-brand conversations.
  2. Ship production systems that handle millions of conversations with rigorous SLOs, fallbacks, and canaries; design graceful degradation (e.g., human handoff) and safety guardrails (prompt-injection, jailbreak, PII redaction).
  3. Lead voice agent initiatives: Drive the development of Uber's voice support agent-covering real-time speech recognition (ASR), text-to-speech, natural turn-taking (barge-in and endpointing), and reliable telephony/WebRTC integration. Ensure low-latency, high-quality interactions that remain robust even in noisy environments.
  4. Advance retrieval & reasoning: Build next-generation retrieval and reasoning pipelines, where the agent can search across different knowledge sources, apply policy-driven tools, and call structured workflows and ensure that responses are consistently grounded.
  5. Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLM-as-judge (with calibrated human review) wired into CI/CD and experiment platforms.
  6. Drive automation at scale: partner with Product/Design/Operations on coverage, policy alignment, localization, and rollout strategy to better customer experience and reduce cost per contact.
  7. Mentor/principal-lead multiple pods; set technical strategy and quality bars; coach senior engineers on agentic patterns, reliability, and experiment velocity.

---- Basic Qualifications ----

  1. 10+ years building production ML/AI systems; 4+ years leading complex ML initiatives end-to-end.
  2. Deep expertise in LLM-driven systems (inference optimization, prompt/program design, fine-tuning, distillation/LoRA, safety/guardrails, evals).
  3. Strong software engineering in Python plus one of Go/Java/C++; hands-on with microservices, gRPC/HTTP, cloud infra, containers, CI/CD, and real-time telemetry/observability.
  4. Demonstrated ownership of high-availability services (SLO/SLA design, incident response, on-call leadership, postmortems).
  5. Track record of shipping customer-facing intelligent experiences with measurable impact (A/B testing, metrics literacy).

---- Preferred Qualifications ----

  1. Voice agent background (ASR/TTS streaming, barge-in, endpointing, telephony, WebRTC) and conversational quality/NLP evaluation. Patterns seen in peer roles emphasize speech + dialog quality as core skills.
  2. Agentic architectures in production (planner/executor, memory, multi-step reasoning) and RAG over complex, policy-heavy knowledge bases.
  3. Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, co-pilot/auto-resolve).
  4. Multilingual NLU/NLG (code-switching, low-resource languages), hallucination mitigation, safety red-teaming, and privacy-by-design.
  5. Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear kill-switches.
  • For San Francisco, CA-based roles: The base salary range for this role is USD**$267,000 per year**
  • USD**$297,000 per year**.
  • 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/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

Uber

Uber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.

10,001+

Employees

San Francisco

Headquarters

$120B

Valuation

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