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motional
Страна
США
Зарплата
142 000 $ – 225 000 $
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SeniorУдалённоПолная занятость

Engineer/Senior Machine Learning Integration Engineer

Оценка ИИ

Отличная вакансия в лидирующей компании в сфере беспилотников с конкурентной зарплатой и возможностью работать над технологиями будущего. Высокий балл за счет сильного бренда (Hyundai/Aptiv) и интересного стека технологий.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью глубоких знаний на стыке ML, робототехники и низкоуровневой оптимизации (C++, CUDA) для систем реального времени. Требуется опыт работы с критически важными для безопасности системами и сложными алгоритмами планирования движения.

Анализ зарплаты

Медиана185 000 $
Рынок150 000 $ – 240 000 $
Оценка ИИ

Предлагаемый диапазон $142k – $225k полностью соответствует рыночным стандартам для Senior ML/Robotics ролей в США, где медиана составляет около $185k. Верхняя граница выше среднего, что отражает высокие требования к специализации.

Сопроводительное письмо

I am writing to express my strong interest in the Machine Learning Integration Engineer position at Motional. With a solid background in deploying ML models onto embedded systems and a deep understanding of both C++ and Python, I am excited about the opportunity to contribute to your motion planning and control stack. My experience in optimizing models for real-time inference using TensorRT and CUDA aligns perfectly with Motional's mission to build safe and efficient autonomous vehicles.

In my previous projects, I have successfully bridged the gap between high-level ML research and low-level hardware constraints, ensuring that complex algorithms run reliably under strict latency requirements. I am particularly drawn to Motional's collaborative environment and its track record of industry-firsts in the robotaxi space. I am confident that my technical skills in reinforcement learning and software engineering, combined with my passion for robotics, will allow me to make an immediate impact on your autonomy team.

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Откликнитесь в motional уже сейчас

Присоединяйтесь к Motional, чтобы внедрять передовые ML-технологии в реальные беспилотные автомобили и менять будущее мобильности!

Описание вакансии

We are seeking a passionate engineer to help bring machine learning–based motion planning to the car. In this role, you will focus on deploying, optimizing, and maintaining ML-driven planning and control algorithms for real-time autonomous driving. You will collaborate across motion planning, controls, and software engineering teams to ensure models run reliably in production, under strict performance and safety constraints.

If you are excited by the challenge of bridging advanced ML with safety-critical, resource-constrained vehicle platforms—and want to shape the future of autonomy—we encourage you to apply.

What You’ll Be Doing

  • Deploy ML-based motion planning and control models onto vehicle platforms, ensuring performance under resource constraints.
  • Optimize models for inference speed, latency, and memory footprint without sacrificing accuracy or safety.
  • Collaborate with motion planning, controls, and perception teams to integrate ML components into the end-to-end autonomous driving stack.
  • Build scalable deployment infrastructure including evaluation pipelines, model packaging, benchmarking, and automated validation.
  • Validate model performance in both simulation and on-road testing, analyzing results and driving iterative improvements.
  • Maintain production-quality code in C++ and Python

What We’re Looking For

  • BS/MS/PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
  • Experience deploying ML systems in real-world robotics, embedded, or autonomous platforms.
  • Experience with reinforcement learning.
  • Strong software engineering skills in C++ and Python, with knowledge of modern development practices (code reviews, testing, CI/CD).
  • Hands-on experience with ML frameworks (PyTorch, TensorFlow) and model optimization for deployment.
  • Familiarity with GPU acceleration, or inference optimization (e.g., TensorRT, CUDA).
  • Strong problem-solving skills and ability to debug complex systems under production constraints.

Bonus Points

  • Experience with autonomous vehicle motion planning, control algorithms (MPC, LQR, PID), or reinforcement learning–based methods.
  • Publications in relevant ML or robotics conferences (ICRA, NeurIPS, CoRL, RSS, etc.).
  • Experience with ROS, AUTOSAR, or other real-time robotics frameworks.
  • Knowledge of numerical optimization and its applications in trajectory generation.

Why You’ll Love Working Here

  • Shape the real-world deployment of cutting-edge ML technology on autonomous vehicles.

Work with world-class ML researchers, software engineers, and controls experts in a highly collaborative environment.

  • Contribute to a mission-driven company building safe, accessible, and transformative mobility solutions.

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. 

Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Salary Range

$142,000—$225,000 USD

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

  • C++
  • Python
  • PyTorch
  • TensorFlow
  • Reinforcement Learning
  • CUDA
  • TensorRT
  • ROS
  • Machine Learning
  • Robotics
  • CI/CD
  • Model Optimization

Возможные вопросы на собеседовании

Проверка навыков оптимизации для работы в реальном времени на ограниченных ресурсах.

Как бы вы подошли к оптимизации задержки (latency) для модели глубокого обучения, развернутой на автомобильной платформе с GPU?

Оценка понимания специфики обучения с подкреплением в контексте управления движением.

С какими основными трудностями вы сталкивались при внедрении алгоритмов Reinforcement Learning в физические робототехнические системы?

Проверка владения C++ в контексте высокопроизводительных систем.

Расскажите о вашем опыте управления памятью и многопоточностью в C++ при разработке систем управления для роботов.

Оценка способности интегрировать ML в классические инженерные пайплайны.

Как обеспечить безопасное взаимодействие между ML-моделью планирования пути и классическим контроллером (например, MPC)?

Проверка навыков отладки сложных распределенных систем.

Опишите процесс отладки ошибки, которая проявляется только при тестировании на реальном автомобиле, но не воспроизводится в симуляции.

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motional
Страна
США
Зарплата
142 000 $ – 225 000 $