Waymo

Waymo

Posted via Greenhouse

Senior ML Compiler Engineer, Compute

Posted Aug 5, 2026

Role at a glance

Salary
Not Disclosed
Location
Bangalore, Karnataka, India
Work arrangement
Hybrid
Employment
Full-time
Education
Bachelor's, Master's, PhD

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Role Summary

AI-generated

The Compute Team develops the compute platform that runs Waymo’s autonomous vehicle software stack, including high-performance custom silicon and system-level compute architectures. This role focuses on compiler performance and support for a high-performance neural network inference platform, collaborating with hardware architects and model developers.

What You'll Do

  • Analyze the performance characteristics of code generated by the production-grade compiler and implement optimizations
  • Design and implement compiler support for novel features of the high-performance architecture
  • Work with hardware architects on hardware/software codesign for the neural network inference platform
  • Work with model developers to tune neural networks for inference efficiency and accuracy

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

C++ programming skills; 3+ years experience working on compilers for parallel architectures; 1+ years experience working with ML inference or linear algebra computation

Required

  • BS degree in Computer Science/Electrical Engineering or equivalent experience
  • MS degree in Computer Science/Electrical Engineering
  • PhD degree in Computer Science/Electrical Engineering
  • 3+ years experience working on compilers for parallel architectures
  • 1+ years experience working with ML inference or linear algebra computation
  • C++ programming skills

Preferred

  • Python programming experience
  • Experience with compilers for neural networks
  • Knowledge of computer architectures used for neural network inference, and neural network performance characteristics
  • Knowledge of the principles behind popular machine learning and neural network algorithms and applications

Original job description

Content provided by the employer

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 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 with many other teammates to ensure we design and improve hardware and software for maximum performance. We are a diverse team looking for 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 a Software Engineering Manager.

This position will require the ability to work some hours that align with the team in the Pacific Time zone on an as needed basis.

You will:

  • Analyze the performance characteristics of code generated by our production grade compiler, and design and implement optimizations to improve that performance
  • Design and implement compiler support for novel features of our high-performance architecture
  • Work with hardware architects to understand and influence the development of our unique neural network inference platform through hardware/software codesign
  • Work with model developers to tune their neural networks for better inference efficiency and accuracy

You have:

  • BS degree in Computer Science/Electrical Engineering or equivalent experience and 5+ years of industry experience OR
  • MS degree in Computer Science/Electrical Engineering and 3+ years of industry experience
  • PhD degree in Computer Science/Electrical Engineering and 1+ years of industry experience
  • 3+ years experience working on compilers for parallel architectures
  • 1+ years experience working with ML inference or linear algebra computation
  • C++ programming skills

We prefer:

  • Python programming experience
  • Experience with compilers for neural networks
  • Knowledge of computer architectures used for neural network inference, and neural network performance characteristics
  • Knowledge of the principles behind popular machine learning and neural network algorithms and applications

 

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
₹6,100,000₹7,250,000 INR
Waymo

About the company

Waymo

Large Enterprise

Waymo is a leading autonomous driving technology company, originally a part of Google's parent company Alphabet Inc. Established in 2009, Waymo focuses on developing self-driving cars and innovative transportation solutions designed to enhance mobility and safety on the roads. By employing advanced artificial intelligence and machine learning algorithms, the company aims to revolutionize personal and shared transportation, making it more accessible and efficient. Waymo's efforts contribute significantly to the future of autonomous vehicles and the ongoing shift towards smart transportation systems.