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Software Engineer, Machine Learning Accelerator

Waymo

Software Engineer, Machine Learning Accelerator

Waymo

Taipei, Taiwan; Hsinchu, Taiwan

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Equity

Bonus

Equity

Required Skills

C

C++

Firmware development

Embedded systems

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.

Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms.

This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Compute team.

You will:

  • Design and implement full stack solution from firmware, low-level drivers, APIs for ML accelerator chips

  • Analyze and optimize firmware and driver performance for demanding AI workloads

  • Collaborate with hardware engineers closely throughout the ASIC design and verification processes

  • Design and implement efficient memory management solutions including NUMA, IOMMU, etc

You have:

  • 3+ years of experience in software development

  • Baremetal or RTOS firmware development experience

  • Experience with embedded architectures, IO technologies (e.g. PCIe, DRAM, AXI, etc.), and hardware/software interactions

  • Strong C, C++ skills

We prefer:

  • Experience with RISC-V architecture

  • Experience with ML frameworks like Tensor Flow or JAX

  • Familiar with hardware-software co-design principles

  • Experience with silicon emulator

The expected base salary range for this full-time position 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. 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**$2,600,000—$3,150,000** TWD

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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%

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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