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waymo
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332 000 $ – 421 000 $
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Principal Software Engineer, ML Flywheel Technical Lead

Оценка ИИ

Исключительная вакансия в одной из ведущих компаний мира в области автономного вождения. Высокая компенсация, работа над передовыми технологиями (L4) и прямое влияние на продукт делают эту роль крайне привлекательной для топ-экспертов.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Это позиция высочайшего уровня (Principal), требующая более 10 лет опыта в ML и глубокой экспертизы в создании инфраструктуры для обучения фундаментальных моделей. Кандидат должен обладать редким сочетанием навыков стратегического лидерства и глубоких технических знаний в области автономного вождения.

Анализ зарплаты

Медиана380 000 $
Рынок320 000 $ – 450 000 $
Оценка ИИ

Предложенная зарплата ($332k - $421k) находится на верхнем уровне рыночных значений для Principal-инженеров в Кремниевой долине. С учетом бонусов и акций (RSU), совокупный доход может значительно превышать средние показатели по рынку.

Сопроводительное письмо

I am writing to express my strong interest in the Principal Software Engineer, ML Flywheel Technical Lead position at Waymo. With over a decade of experience in machine learning and a proven track record of architecting large-scale production systems, I am eager to contribute to Waymo's mission of building the world's most trusted driver. My background in developing foundation models and managing end-to-end ML lifecycles aligns perfectly with your goal of creating an automated, data-driven self-improvement loop.

In my previous roles, I have successfully led technical teams to bridge the gap between complex infrastructure and high-quality model performance. I am particularly drawn to Waymo's challenge of transforming every autonomous mile into a valuable data point for continuous learning. I am confident that my expertise in multi-modal models and systematic data curation will help accelerate the velocity and impact of the Waymo Driver's development.

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Откликнитесь в waymo уже сейчас

Присоединяйтесь к Waymo, чтобы возглавить разработку технологий автономного вождения будущего и масштабировать ML-маховик мирового уровня.

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.

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.

Every mile driven by a Waymo car is a unique and valuable piece of data that can be leveraged into improving our machine learning models, and ultimately the safety and capabilities of the Waymo Driver. Charting the path from collection of a piece of data, to curation, (auto-)labeling, model training and evaluation, all the way to model deployment and monitoring is a process of continuous scaling and quality improvement of the entire ML lifecycle. The Area Technical Lead for the Waymo machine learning flywheel is responsible for architecting, connecting, automating and improving the entire span of this self-improvement process in close collaboration with Waymo’s infrastructure, modeling and evaluation teams. They are directly accountable to Waymo’s leadership for the organization’s ML data strategy and its impact on Driver quality.

You will report directly to our Distinguished Engineer, Foundation Models.

You Will:

  • Architect a path towards every autonomous mile driven by a Waymo car to be automatically incorporated into an automated data-driven self-improvement loop for the Waymo Driver.
  • Enable a data flywheel to serve the demands of scalable pre-training, post-training targeted to relevant critical behaviors, as well as Driver simulation and validation.
  • Enable a modeling flywheel to efficiently consume that data to reliably generate updated models that are validated and deployable with minimal human toil.
  • Coordinate cross-functional efforts in partnership with data and ML infrastructure teams, resource planning, logging infrastructure, modeling and validation teams to accelerate the velocity, impact and leverage of driving data on the Waymo Driver.
  • Act as the steward of data quality, by providing tooling and metrics to evaluate the impact of mining, selection and curation on the modeling pipeline performance.
  • Articulate the strategy for incorporating diverse data sources, including third-party and synthetic data into that improvement flywheel.
  • Drive innovation across all axes of performance and efficiency, from Driver quality, to scalability, cost, engineering velocity, model architecture and performance.

You Have:

  • Master's degree or PhD in Computer Science, Engineering, or a related technical field
  • 10+ years of experience in ML model development, and you have 2+ years experience with large-scale vision, video, or multi-modal foundation model development and their integration in end-to-end models
  • 6+ years of experience in ML-driven production systems that develops models with large-scale data, training, evaluation, and deployment
  • 6+ years of experience in a technical leadership role leading technical teams and setting technical directions in large ML Engineering organizations
  • Demonstrated expertise in large-scale machine learning and its key components: pre-training, post-training, and validation. Deep understanding of both infrastructure and quality aspects.
  • Track record of architecting and standing up a machine learning flywheel at scale for mission critical applications.
  • Experience with driving model quality improvements through systematic data scaling and curation.
  • Communication and interpersonal skills. Ability to inspire, influence and coordinate across functions and disciplines.

We Prefer:

  • PhD in computer science.
  • Experience in multi-modal LLM model development, and their infrastructure.
  • Familiarity with multi-task, end-to-end models and their development challenges.

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

$332,000—$421,000 USD

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Python
  • Machine Learning
  • Computer Vision
  • Deep Learning
  • MLOps
  • Scalability
  • Distributed Systems
  • Robotics
  • Data Curation
  • Foundation Models

Возможные вопросы на собеседовании

Кандидат должен понимать, как эффективно отбирать данные для обучения из огромного потока сырых данных.

Как бы вы спроектировали систему автоматической курации данных для ML-маховика, чтобы минимизировать шум и максимизировать влияние на качество вождения?

Роль требует координации между командами инфраструктуры, моделирования и валидации.

Опишите ваш опыт руководства кросс-функциональными инициативами: как вы разрешаете конфликты между требованиями к скорости разработки и стабильностью инфраструктуры?

Waymo активно использует симуляции для обучения.

Какую роль, по вашему мнению, должны играть синтетические данные в сравнении с реальными данными с дорог в контексте обучения фундаментальных моделей для L4 автопилота?

Позиция подразумевает работу с Foundation Models.

С какими основными трудностями вы сталкивались при масштабировании мультимодальных моделей (vision/video) для работы в реальном времени?

Важно понимать, как кандидат оценивает успех всей системы.

Какие ключевые метрики (KPI) вы бы внедрили для оценки эффективности ML-маховика, помимо стандартных метрик точности моделей?

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W
waymo
Страна
США
Зарплата
332 000 $ – 421 000 $