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Software Quality Ops Scenarios Specialist

Waymo

Software Quality Ops Scenarios Specialist

Waymo

Mountain View, CA

·

On-site

·

Full-time

·

1w ago

Compensation

$120,000 - $151,000

Benefits & Perks

Equity

401(k)

Equity

401k

Required Skills

ML testing

Quality assurance

Root cause analysis

Technical troubleshooting

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The Software Quality Operations (SWQOps) team is at the heart of ensuring the safety, reliability, and quality of the Waymo Driver. Our mission is to build an adaptable and scalable operation, increasingly powered by AI, to deliver the crucial insights necessary to confidently deploy and grow Waymo's autonomous vehicle service.

Why This Team is Essential to Waymo's Success:

Waymo is undergoing unprecedented growth, rapidly expanding into new cities (targeting ~20 new cities by EOY 2026) and launching new vehicle platforms. SWQ Ops plays a critical role in this expansion, making it possible to scale safely and efficiently. The Scenario Operations team within SWQ Ops owns the scaled delivery and maintenance of simulation-based directed testing coverage used to evaluate the Safety and performance of the driver as Waymo continues to scale. As a Technical Specialist in Scenario Operations, you are the Subject Matter Expert who bridges the gap between our simulation software capabilities and real-world operational execution.

You will:

  • Tooling Development & Optimization: Partner with Product and Engineering teams on design, test, and deployment of cutting-edge simulation tools. You will ensure these tools effectively combine human-in-the-loop (HITL) precision with AI-driven automation to create scalable test coverage.

  • Rapid Issue Response: Drive the technical processes for "rapid-response" simulation-based scenario testing. When emergent issues are found in the field, you will apply your deep understanding of the A/V software stack and our tooling to support root-cause evaluation and fix validation.

  • Policy Development: Serve as the key link between AI/ML development and operational execution. Define and document new policies, guidelines, and Standard Operating Procedures (SOPs) that integrate advanced tools and insights into daily vendor workflows.

  • Quality Assurance: Design and implement robust quality control processes for both human and AI-generated outputs. Perform meta-quality checks, validate the integrity of vendor work, and provide feedback to improve both human and model performance.

  • Technical Consultation: Act as the Subject Matter Expert (SME) for your specific domain. You will provide technical leadership to cross-functional stakeholders, advising on the feasibility of new testing coverage and driving tool improvements to achieve desired outcomes.

You have:

  • BS/BA degree or 4 years of relevant work experience in AV Software Quality, Simulation or Technical Operations

  • Experience with ML testing and validation methods, including dataset quality assurance, bias detection, edge-case scenario testing, and / or performance evaluation using statistical metrics.

  • Ability to quickly master proprietary software tools and a proven track record of root-causing high complexity, technical issues

  • A strong understanding of driving rules, behavioral safety, and the nuances of complex traffic environments

We prefer:

  • Hands-on experience with advanced AV simulation test environments

  • Basic experience with SQL for data extraction and basic results analysis

  • Experience working with offshore teams / multiple local operations hubs

  • Track record of using technical expertise to influence product roadmaps or improve internal customer satisfaction.

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range**$120,000—$151,000 USD**

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About Waymo

Waymo

Waymo LLC is an American autonomous driving technology company headquartered in Mountain View, California. It is a subsidiary of Alphabet Inc., Google's parent company.

1,001-5,000

Employees

Mountain View

Headquarters

$200B

Valuation

Reviews

4.2

2 reviews

Work Life Balance

3.5

Compensation

3.0

Culture

4.5

Career

3.5

Management

3.5

85%

Recommend to a Friend

Pros

Excellent engineering culture

Interesting technical domain

Elite perception team

Cons

Compensation may not be competitive with other tech companies

Career trajectory concerns

Limited advancement opportunities

Salary Ranges

1,233 data points

Mid/L4

Mid/L4 · Data Scientist

38 reports

$280,748

total / year

Base

$183,551

Stock

$74,549

Bonus

$22,649

$187,768

$434,285

Interview Experience

5 interviews

Difficulty

3.6

/ 5

Duration

14-28 weeks

Offer Rate

60%

Experience

Positive 40%

Neutral 60%

Negative 0%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Coding Round

5

Onsite/Virtual Interviews

6

Final Round

Common Questions

Coding/Algorithm

Machine Learning

System Design

Behavioral/STAR

Technical Knowledge