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Research Scientist, Robotics
Это вакансия мечты для любого исследователя в области ИИ: работа в Google DeepMind над проектами мирового уровня (Gemini Robotics) с доступом к неограниченным вычислительным ресурсам.
Сложность вакансии
Чрезвычайно высокая сложность из-за требований к ученой степени (PhD), глубоких знаний в области RL/VLA и необходимости работать на переднем крае науки в одной из ведущих ИИ-лабораторий мира.
Анализ зарплаты
Зарплаты в Google DeepMind в Лондоне являются одними из самых высоких на рынке, часто включая значительные пакеты акций (RSU) и бонусы, что ставит их выше среднего уровня по Великобритании.
Сопроводительное письмо
I am writing to express my strong interest in the Research Scientist, Robotics position at Google DeepMind. With a deep background in reinforcement learning and experience in developing large-scale multimodal models, I have long admired DeepMind’s commitment to pushing the boundaries of Artificial General Intelligence. My research focus aligns perfectly with your work on Gemini Robotics and Vision-Language-Action (VLA) models, particularly in bridging the gap between high-level reasoning and low-level physical control.
In my previous work, I have successfully implemented scalable machine learning algorithms and worked extensively with both simulated environments and real-world robotic platforms. I am particularly excited by the prospect of working on agentic systems that can reason over long multi-step tasks and achieve high dexterity. I am confident that my technical expertise in imitation learning and my passion for embodied AI would allow me to contribute significantly to your mission of bringing advanced AI to the physical world.
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Откликнитесь в deepmind уже сейчас
Присоединяйтесь к команде Google DeepMind, чтобы создавать будущее робототехники и воплощать ИИ в физическом мире!
Описание вакансии
Snapshot
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
About Us
At Google DeepMind Robotics we are pioneering bringing AI to the physical world. We are powering an era of physical agents, enabling robots to perceive, plan, think, use-tools, and act to better solve complex tasks.
What we do:
- Building foundation models: We develop advanced Vision Language Action (VLA) models that combine Gemini's world understanding with physical actions to directly control robots. These models include Gemini Robotics (our most advanced Gemini model for the physical world), and Gemini Robotics On-Device (our fastest Gemini model that runs without a data network). We also develop advanced reasoning and agentic systems for the physical world, including: Gemini Robotics-ER, a Gemini agent with advanced spatial understanding and agentic reasoning. These models enable robots to perform a broad range of tasks, respond interactively to their environment, achieve high dexterity, and reason over long multi-step tasks.
- Advance the state of the art: We are always focused on advancing the state-of-the-art in all areas of general purpose robotics, including agentic reasoning, real world understanding, action generalization, human robot interaction, dexterity, whole-body-control, continual learning, and more.
- Deploy at scale: We partner with key robotics companies to bring this intelligence to the physical world across a broad range of applications at scale.
The Role
Research Scientists lead our efforts in developing novel algorithms and models for embodied AI and Artificial General Intelligence. We are looking for creative thinkers with strong algorithm-design and programming skills that want to build the next generation of AI agents for and grounded in the physical world. Research Scientists work in collaborative teams to invent algorithms and innovate on large foundation models such as Gemini Robotics. They design prototype applications and work with real robots inside and outside the lab to tackle real-world use cases. A strong algorithmic background in scalable machine learning (e.g. reinforcement learning / imitation learning; multimodal foundation models) and experience with real robots / robot simulation and large-scale training setups are valued.
Key responsibilities:
- Design, implement, train and evaluate large models and algorithms for robotic agents. Make breakthroughs and unlock new robot capabilities.
- Write software to implement research ideas and iterate quickly.
- Leverage your expertise to participate in a wide variety of research: learning from simulation, reinforcement learning, learning from demonstrations, vision-language-action models, transformers, video generation, robot control, humanoid robots and more.
- Work effectively with a large collaborative team with fast-paced agendas to meet ambitious research goals.
- Generate creative ideas, set up experiments and test hypotheses. Report and present research findings clearly and efficiently both internally and externally.
About You
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- PhD in a technical field or equivalent practical experience.
- A strong algorithmic background with deep knowledge of areas such as
- reinforcement learning and imitation learning
- multimodal generative modeling, training and inference.
- large vision / vision-language / video and other multimodal models
In addition, the following would be an advantage:
- Experience working with simulators and real-world robots, esp. dexterous manipulation including multi-fingered hands and / or whole body control, as well as multimodal sensing (e.g. tactile)
- Experience implementing large-scale systems and working with large real world data
- A passion for bringing research from the lab to real-world robotic systems.
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
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Навыки
- Python
- Machine Learning
- Computer Vision
- Deep Learning
- Transformers
- Robotics
- Simulation
- Natural Language Processing
- Algorithms
- Reinforcement Learning
Возможные вопросы на собеседовании
Проверка глубины знаний в ключевой технологии DeepMind для робототехники.
Как бы вы подошли к архитектуре Vision-Language-Action (VLA) модели для обеспечения обобщения на новые, ранее не виденные задачи манипуляции?
Оценка практического опыта работы с реальным оборудованием и понимания разрыва между симуляцией и реальностью.
С какими основными трудностями вы сталкивались при переносе политик обучения с подкреплением (RL) из симуляции на реальных роботов (Sim-to-Real), и как вы их решали?
Проверка навыков работы с масштабными системами, что критично для моделей семейства Gemini.
Опишите ваш опыт масштабирования обучения моделей на больших кластерах. Какие узкие места возникают при обучении трансформеров для управления роботами в реальном времени?
Оценка способности к долгосрочному планированию в робототехнике.
Как интегрировать высокоуровневое логическое рассуждение (reasoning) из LLM в низкоуровневое управление роботом для выполнения многоэтапных задач?
Проверка навыков командной работы в исследовательской среде.
Расскажите о случае, когда ваша исследовательская гипотеза не подтвердилась. Как вы адаптировали свой подход и взаимодействовали с командой в этой ситуации?
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