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Staff Software Engineer, Map Semantics

Оценка ИИ

Высокопрестижная позиция в лидирующей компании в сфере беспилотников (JV Hyundai и Aptiv). Работа над передовыми технологиями в Сингапуре с сильной инженерной культурой и возможностью влиять на индустрию.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует исключительной квалификации: ученой степени (Masters/PhD), более 7 лет опыта и глубоких знаний в узких областях, таких как 3D-детекция и семантическая сегментация. Дополнительную сложность добавляет требование к наличию публикаций на топовых конференциях (CVPR, ICML).

Анализ зарплаты

Медиана160 000 $
Рынок130 000 $ – 200 000 $
Оценка ИИ

Указанный диапазон соответствует рыночным ставкам для позиций уровня Staff/Principal Engineer в технологическом секторе Сингапура. Учитывая статус компании как совместного предприятия гигантов индустрии, можно ожидать компенсацию по верхней границе рынка, включая бонусы и акции.

Сопроводительное письмо

I am writing to express my strong interest in the Staff Software Engineer position within the Map Semantics team at Motional. With over 7 years of experience in developing machine learning solutions and a deep background in 3D object detection and scene understanding, I am eager to contribute to your mission of making Level 4 autonomous driving a reality. My expertise in productionizing ML models using PyTorch and Python, combined with a solid understanding of multi-modal sensor data, aligns perfectly with Motional's technical requirements.

Throughout my career, I have focused on designing scalable ML architectures that bridge the gap between research and real-world deployment. I am particularly impressed by Motional's track record, including the world's first robotaxi pilot, and I am excited by the challenge of geometrically representing environments to enhance localization and mapping. I am confident that my experience in metrics-driven development and my passion for autonomous robotics will allow me to make a significant impact on your autonomy stack.

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Откликнитесь в motional уже сейчас

Присоединяйтесь к Motional, чтобы создавать будущее автономного транспорта и внедрять ML-решения мирового уровня в Сингапуре!

Описание вакансии

On our Map Semantics team, you will have the opportunity to work with world-class machine learning (ML) engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The team develops ML models that detect fixed, semantic objects in multi-modal data, enabling mapping and real-time localization.  These objects include lane lines, stoplights, traffic signs and other structures in the built environment.  We are looking for proven technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:

  • Define and execute projects focused on scene understanding to geometrically represent the environment. These representations will enhance the efficiency of our self-driving vehicle’s capability to map roadways and localize itself using both autonomous vehicle and remote sensing data.
  • Develop machine learning models to reliably and efficiently detect the built environment using single or multi-modal sensor data including vision, LIDAR, and RADAR
  • Productionize and deploy solutions onto autonomous vehicle fleets
  • Collaborate with localization, mapping and perception teams to improve  your products’ on-road performance

What We’re Looking for:

  • Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
  • 7+ years of professional software engineering experience.
  • Solid experience in real time 3D Object Detection, Semantic Segmentation or Scene element detection

Experience working with large scale multi-modal datasets.

  • Experience with deep learning frameworks such as TensorFlow or PyTorch
  • Fluency in Python, including standard scientific computing libraries
  • Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
  • Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
  • Extensive experience in metrics design and metrics driven technology development
  • Excellent communication and interpersonal skills
  • Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, WACV, AAAI, ICL, etc.)

Bonus Points:

  • Familiarity with multi-view geometry, factor graph optimization / bundle adjustment
  • Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
  • Remote sensing experience including geospatial coordinate frames, object detection, RPC camera models
  • Experience with change detection and updating maps based on newly collected data
  • Experience with un/self/semi/weakly-supervised learning techniques
  • Strong programming skills in C++

Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.

Our journey is always people first.

We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.

Higher purpose, greater impact.

We’re creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it’s not only good for our business, it’s the right thing to do.

Scale up, not starting up.

Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.

Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit  www.Motional.com and follow us on Twitter, LinkedInInstagram and YouTube.

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

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Навыки

  • Python
  • PyTorch
  • TensorFlow
  • C++
  • Machine Learning
  • Computer Vision
  • 3D Object Detection
  • Semantic Segmentation
  • LiDAR
  • Radar
  • Deep Learning
  • Software Design
  • Source Control

Возможные вопросы на собеседовании

Проверка глубины знаний в основной области ответственности команды.

Как бы вы подошли к задаче объединения данных от LIDAR и камер для точной семантической сегментации дорожной разметки в реальном времени?

Важно понимать, как кандидат оценивает качество моделей в контексте беспилотного вождения.

Какие специфические метрики, помимо mAP, вы бы использовали для оценки надежности детекции стоп-линий и светофоров?

Позиция Staff предполагает умение доводить исследования до продакшена.

Опишите ваш опыт оптимизации тяжелых Deep Learning моделей для работы на встраиваемых системах с ограниченными ресурсами.

Проверка навыков работы с геометрией, что критично для задач маппинга.

Как вы учитываете неопределенность (uncertainty) в предсказаниях модели при передаче данных в модули локализации и построения карт?

Оценка научного вклада и умения следовать SOTA-подходам.

Расскажите о вашей наиболее значимой публикации или исследовании: какую проблему вы решали и как это применимо к задачам Motional?

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motional
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