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- 200 000 $ – 240 000 $
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Staff AI Researcher / Engineer
Исключительная вакансия в сфере DeepTech с конкурентной зарплатой и возможностью работать над инновационным продуктом (электрические самолеты). Высокий балл за амбициозность задач и четко прописанный стек технологий.
Сложность вакансии
Высокая сложность обусловлена требованиями к глубоким научным знаниям (PhD/MS), 8+ годам опыта и экспертизе в сложнейших темах, таких как VLA-модели и диффузионные политики. Роль требует совмещения навыков исследователя и инженера в высокотехнологичной аэрокосмической отрасли.
Анализ зарплаты
Предлагаемая зарплата ($200k - $240k) полностью соответствует рыночным стандартам для позиции уровня Staff AI Engineer в Кремниевой долине, где медиана составляет около $225k. Диапазон Archer является конкурентоспособным для аэрокосмического сектора.
Сопроводительное письмо
I am writing to express my strong interest in the Staff AI Researcher / Engineer position at Archer. With over 8 years of experience in machine learning and a deep focus on transformer architectures and multi-modal models, I am excited by the prospect of applying these technologies to the challenge of sustainable air mobility. My background in developing production-ready AI systems and my commitment to rigorous research align perfectly with Archer's mission to build the next generation of electric aircraft.
Throughout my career, I have specialized in bridging the gap between academic research and practical implementation. I have extensive experience with PyTorch and have led projects involving model distillation and fine-tuning for complex robotic applications. I am particularly drawn to Archer's focus on VLA models and reinforcement learning, as I believe these are key to achieving the level of autonomy and safety required for urban air mobility. I look forward to the possibility of contributing to your innovative team in San Jose.
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Описание вакансии
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
What You’ll Do:
You are a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:
- Design, implement, and evaluate novel machine learning and deep learning algorithms.
- Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment.
- Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
- Conduct experiments to benchmark new techniques and evaluate model behavior.
- Develop tools and frameworks to support scalable and reproducible research and development.
- Communicate research findings to leadership in a concise, and convincing manner.
- Stay current with the latest developments in AI/ML and identify relevant innovations.
- Assist in transitioning research prototypes into production-ready systems.
What You Need:
- 8+ years of relevant experience, with strong emphasis on AI and ML
- M.S or PhD degree in Computer Science, or Computer Engineering
- Enjoys solving less-defined and complex problems
- Familiarity with good SW practices and development, including code quality, version control, etc.
- Very strong with ML frameworks such as Pytorch, or Tensorflow
- Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
- Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
- Is up to date with research literature and recent ML techniques and methodologies.
Bonus Qualifications:
- Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
- Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
- Experience developing production AI models is a plus.
- Publications at top conferences are a plus.
Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $200,000.00 - $240,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.
Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.
Information collected and processed as part of any job applications you choose to submit is subject to Archer's Candidate Privacy Policy.
Archer is unable to provide work visa sponsorship for this position at the present time.
Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.
Archer Aviation does not engage with external recruiting agencies/individual recruiters with whom it does not have a prior written agreement. Archer reserves the right to make use of any unsolicited resumes that it receives and bears no responsibility for payment of any fees asserted from the use of unsolicited resumes. If you are a recruiting agency or individual recruiter wishing to do business with Archer, please reach out to People@archer.com. All employment processes are managed by the Archer People Team.
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Навыки
- Python
- PyTorch
- Machine Learning
- Computer Vision
- Deep Learning
- Transformers
- TensorFlow
- Robotics
- Natural Language Processing
- Reinforcement Learning
Возможные вопросы на собеседовании
Проверка глубины понимания архитектур, указанных в требованиях.
Как бы вы оптимизировали механизм внимания в Transformer для работы с длинными последовательностями данных в реальном времени на борту самолета?
Оценка опыта в области мультимодального обучения, важного для автономных систем.
Какие основные трудности возникают при обучении Vision-Language-Action (VLA) моделей для задач мобильности и как вы их решали?
Проверка навыков отладки и работы с данными.
Опишите ваш процесс отладки нейросети, которая показывает хорошие результаты на валидации, но ведет себя нестабильно в симуляции или реальной среде.
Оценка способности внедрять научные достижения в продукт.
Расскажите о случае, когда вы успешно перенесли алгоритм из академической статьи в продакшн-систему. С какими инженерными вызовами вы столкнулись?
Проверка знаний в области обучения с подкреплением (RL).
В каких случаях для управления БПЛА вы бы предпочли Imitation Learning вместо Reinforcement Learning, и наоборот?
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- Страна
- США
- Зарплата
- 200 000 $ – 240 000 $