- Страна
- США
- Зарплата
- 204 000 $ – 259 000 $
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Senior Machine Learning Engineer, Perception LLM/VLM
Исключительная вакансия в одной из лидирующих компаний мира в сфере беспилотного транспорта. Высокая зарплата, работа с уникальными данными и возможность влиять на безопасность дорожного движения делают эту позицию топовой на рынке.
Сложность вакансии
Роль требует глубокой экспертизы в области LLM/VLM, опыта работы с огромными массивами данных и владения специфическими фреймворками вроде Jax. Высокий порог входа обусловлен необходимостью совмещать исследовательскую деятельность с внедрением моделей в реальный продукт (автопилот).
Анализ зарплаты
Предложенная зарплата ($204k - $259k) полностью соответствует и даже немного превышает рыночные стандарты для Senior ML ролей в Кремниевой долине, особенно учитывая дополнительные бонусы и акции (RSU).
Сопроводительное письмо
I am writing to express my strong interest in the Senior Machine Learning Engineer position within the Perception team at Waymo. With over five years of experience in developing large-scale machine learning models and a deep expertise in VLM pre-training and continual learning, I am eager to contribute to the mission of building the world's most trusted driver. My background in optimizing complex multimodal data streams and my proficiency in Jax and PyTorch align perfectly with Waymo's cutting-edge approach to autonomous perception.
In my previous roles, I have successfully implemented large-scale training pipelines and conducted research that translated into production-ready systems. I am particularly drawn to Waymo's unique access to millions of miles of real-world driving data, which provides an unparalleled environment for advancing foundation models. I am confident that my technical skills in model evaluation and my passion for solving real-world robotics challenges will allow me to make a significant impact on the Waymo Driver's spatial-temporal understanding.
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Откликнитесь в waymo уже сейчас
Присоединяйтесь к команде Waymo и создавайте будущее автономного вождения с помощью передовых VLM-моделей!
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 Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.
You will:
- Design, implement, and optimize large-scale continual pre-training pipelines for cutting-edge VLM foundation models.
- Conduct research and development on novel pre-training techniques, focusing on efficiently integrating new, diverse, and multimodal data streams (e.g., visual data from different sensors) into existing models.
- Develop and rigorously evaluate metrics and methodologies for measuring the performance, and transferability of continually pre-trained foundation models in the context of autonomous driving.
- Stay current with the latest advancements in large language models, vision-language models, and continual learning, and translate relevant research into production-ready systems.
You have:
- 5+ years of experience in Machine Learning, with a focus on large-scale model development (LLM, VLM, or similar foundation models).
- Proven expertise in LLM/VLM pre-training, continual learning with large scale datasets.
- Strong coding proficiency in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch).
- Hands-on experience with model training, evaluation, and deployment in a production environment.
- Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
We prefer:
- Experience in fine-tuning foundation models for autonomous driving or robotics applications
- Familiarity with large-scale data curation and quality assurance processes for multimodal datasets.
- Background in autonomous vehicle perception, motion planning, or decision-making systems.
- Publications in top-tier machine learning or computer vision conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
- PhD in a relevant field.
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
- Machine Learning
- LLM
- JAX
- Computer Vision
- Deep Learning
- TensorFlow
- Multimodal Learning
- VLM
- Continual Learning
Возможные вопросы на собеседовании
Проверка опыта работы с архитектурами, указанными в описании вакансии.
Опишите ваш опыт проектирования пайплайнов для предварительного обучения (pre-training) VLM: с какими основными трудностями при масштабировании вы сталкивались?
Вакансия делает акцент на непрерывном обучении (continual learning).
Как вы решаете проблему 'катастрофического забывания' при дообучении больших моделей на новых потоках данных из сенсоров?
Waymo использует Jax и TensorFlow; важно понимать владение инструментарием.
В чем, по вашему мнению, основные преимущества и недостатки использования Jax по сравнению с PyTorch при обучении гигантских моделей на кластерах TPU?
Для беспилотников критична точность и переносимость моделей.
Какие метрики вы бы предложили для оценки качества 'spatial-temporal representation' в контексте безопасности движения?
Проверка навыков работы с данными, что критично для Perception.
Как вы организуете процесс фильтрации и обеспечения качества (QA) для терабайтов мультимодальных данных перед подачей в обучающий пайплайн?
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- Страна
- США
- Зарплата
- 204 000 $ – 259 000 $