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JobsNVIDIA

Manager, Autonomous Vehicle Fleet Operation

NVIDIA

Manager, Autonomous Vehicle Fleet Operation

NVIDIA

China, Shanghai

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Comprehensive health, dental, and vision insurance

Parental leave

Team events and activities

Competitive salary and equity package

401(k) matching

Healthcare

Parental Leave

Equity

Required Skills

TypeScript

Python

PostgreSQL

NVIDIA is seeking a AV Fleet Operation Manager to drive end-to-end improvements of our autonomous vehicle test fleet operation and launch a great autonomous driving experience to millions of users around the world! You will participate in a focused effort to productize ground-breaking solutions that will redefine the world of transportation and the growing field of self-driving cars. You will work with hardworking and dedicated multi-functional engineering development teams across various vehicle subsystems to integrate their work into our autonomous DRIVE SW platform, while achieving or exceeding all relevant NVIDIA and automotive standards & guidelines. You'll find the work is exciting, fun, and meaningful. We have customers, and competition. Come join the team and see how you can make a lasting impact on the world.

What you will be doing:

  • Lead a team of engineers, drivers, test operators to bringup and maintenance a fleet of AV test vehicle; carry out tests and generate data and test results along with other teams.

  • Coordinate among requesting teams to plan test resources, track progress to ensure test resource availability

  • Oversee test execution team, understand test requirements. Guide execution to provide quality test results.

  • Identify resource gap, collaborate and negotiate with partners and suppliers to acquire resources, e.g. test vehicles, contractors, facilities.

  • Lead the fleet efficiency across car, garage, people and execution. Drive it to the Speed of light. Own/ Raise and drive major gaps and failures through systemic improvements.

  • Ensure that the driving quality of the fleet engineering remains optimized by making go/no-go decisions on major technical changes, defining the tests/frameworks required to guard against regressions, and identifying/addressing regressions.

  • Scale out this iterative development process by developing more automation and leveraging from current operational teams/resources.

What we need to see:

  • Bachelors or a higher degree (or equivalent experience) in Computer Science or a related field

  • 10+ overall years of experience in a similar or related role, with 4 years of leadership experience leading engineers and contractors

  • Practical experience working in Linux, using version control systems, and debugging

  • Well-rounded knowledge of how an autonomous vehicle stack works, and practical experience dealing with the challenges in this area

  • Strong leadership and interpersonal skills, with the ability to drive alignment across large organizations

Ways to stand out from the crowd:

  • Background with autonomous vehicle and/or machine learning development

  • Experience with data analysis tools/languages

  • Experience with start-ups and/or early-stage products

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About NVIDIA

NVIDIA

NVIDIA

Public

A computing platform company operating at the intersection of graphics, HPC, and AI.

10,001+

Employees

Santa Clara

Headquarters

$4.57T

Valuation

Reviews

4.1

10 reviews

Work Life Balance

3.5

Compensation

4.2

Culture

4.3

Career

4.5

Management

4.0

75%

Recommend to a Friend

Pros

Great culture and supportive environment

Smart colleagues and excellent people

Cutting-edge technology and learning opportunities

Cons

Team-dependent experience and outcomes

Work-life balance issues with long hours

Politics and influence over competence

Salary Ranges

47 data points

Junior/L3

Mid/L4

Junior/L3 · Analyst

7 reports

$170,275

total / year

Base

$130,981

Stock

-

Bonus

-

$155,480

$234,166

Interview Experience

7 interviews

Difficulty

3.1

/ 5

Experience

Positive 0%

Neutral 86%

Negative 14%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

System Design Interview

6

Team Review

Common Questions

Coding/Algorithm

System Design

Technical Knowledge

Behavioral/STAR