- Страна
- США
- Зарплата
- 204 000 $ – 259 000 $
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Machine Learning Engineer, Simulation Realism
Исключительная вакансия в одной из ведущих компаний мира в сфере беспилотного транспорта. Высокая зарплата, работа с передовыми технологиями (GenAI, World Models) и значительное влияние на безопасность продукта.
Сложность вакансии
Высокая сложность обусловлена требованиями к глубоким знаниям в области GenAI, Foundation Models и опытом работы с крупномасштабными кластерами GPU/TPU. Также требуется сильный бэкграунд в C++ для продакшн-среды.
Анализ зарплаты
Предлагаемый диапазон $204k–$259k полностью соответствует рыночным стандартам для Senior/Staff ML ролей в Кремниевой долине. Верхняя граница даже несколько превышает медиану для аналогичных позиций в Tier-1 компаниях.
Сопроводительное письмо
I am writing to express my strong interest in the Machine Learning Engineer position within the Simulation Realism team at Waymo. With over five years of experience in developing large-scale ML models and a deep background in Python and PyTorch, I have consistently focused on bridging the gap between research and production-ready software. My expertise in Generative AI and foundation models aligns perfectly with Waymo's mission to enhance simulation fidelity through advanced world modeling.
In my previous roles, I have successfully trained models on large GPU/TPU clusters and integrated complex ML components into production systems. I am particularly drawn to Waymo's collaborative environment and the opportunity to work on embodied agents and counterfactual scenarios. I am confident that my technical skills in C++ and my passion for autonomous vehicle technology will allow me to contribute significantly to the realism and steerability of your simulation platforms.
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Откликнитесь в waymo уже сейчас
Присоединяйтесь к Waymo, чтобы создавать будущее автономного вождения с помощью передовых технологий генеративного ИИ!
Описание вакансии
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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Our team is a diverse and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions.
To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundational World Model trained on our datasets, world understanding and reasoning capabilities for tail cases, and reinforcement learning for long term credit assignment. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple counterfactual scenarios to rigorously test our autonomous driving systems.
In this hybrid role, you will report to a Senior Staff Tech Lead Manager
You will:
- Drive innovation in ultra-realistic world simulation for autonomous vehicles. You will develop the latest simulation technologies using foundation models for embodied agents.
- Apply your deep Machine Learning (ML) expertise, in Generative AI (GenAI), to push the boundaries of simulation realism and directly influence the advancement of autonomous driving technology.
- Work with Waymo's foundational AI research team to transfer research into scalable and production-ready solutions.
You have:
- 5+ years of experience with ML software engineering
- 5+ years of experience with Python
- 5+ years of ML software experience with machine learning framework including Pytorch, Tensorflow, Jax/Flax ,
We prefer:
- Experience working with, creating and/or developing ML models for robotics and/or self driving vehicles
- Strong C++ in production setting, with experience in integrating ML models in production system
- Experience in training large scale models on GPU/TPU clusters are strongly preferred
#LI-Hybrid
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
$204,000—$259,000 USD
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- PyTorch
- TensorFlow
- JAX
- Flax
- C++
- Generative AI
- Reinforcement Learning
- Machine Learning
- Computer Vision
- Distributed Training
Возможные вопросы на собеседовании
Проверка понимания специфики работы с симуляциями для беспилотников.
Как бы вы подошли к оценке реализма поведения агентов (автомобилей и пешеходов) в симуляции по сравнению с реальными данными?
Оценка опыта работы с современными архитектурами, упомянутыми в вакансии.
Какие основные проблемы возникают при обучении World Models для задач автономного вождения и как их решать?
Проверка навыков оптимизации и работы с инфраструктурой.
Опишите ваш опыт масштабирования обучения моделей на распределенных кластерах (GPU/TPU). С какими узкими местами вы сталкивались?
Важно для интеграции моделей в систему симуляции.
Расскажите о вашем опыте интеграции ML-моделей, написанных на Python/PyTorch, в высокопроизводительную среду на C++.
Проверка навыков работы с обучением с подкреплением, упомянутым в описании.
Как можно использовать Reinforcement Learning для решения проблемы долгосрочного распределения вознаграждения (long-term credit assignment) в сценариях симуляции?
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- Страна
- США
- Зарплата
- 204 000 $ – 259 000 $