Motional

Senior Principal Radar Autonomy Engineer

United States

Not SpecifiedCompensation
Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Automotive, Artificial Intelligence, RoboticsIndustries

About the Role

We are looking to add a talented Principal Radar Autonomy Engineer to join our Autonomy team. You will own developing state-of-the-art Radar systems, including hardware design, data processing, and developing machine learning models to ingest low-level radar data. You will work closely with a cross-functional team to enable the entire sensor suite to empower end-to-end machine learning. As a hands-on engineering lead, you will architect and co-develop both Radar sensors and machine learning pipelines to drive our next-generation vehicles. Your deep applied research experience will inform your visionary approach to enable more intelligent, capable, and cost-effective autonomous vehicles, and your deep engineering experience will enable pragmatic trade-off decisions. We are looking for someone that knows how to push the boundary of “the box”, and thrives working as the technical expert across both the hardware and software domains.

What You'll Be Doing

  • Applied research and development of deep neural networks for end-to-end solutions.
  • Own and deliver state-of-the-art Imaging Radar hardware and machine learning to push the performance boundaries for next-generation Autonomous Vehicles.
  • Develop core deep learning codebase for efficient training and testing pipelines.
  • Conduct deep learning experiments, write reports / publications, and file patents.
  • Work cross-functionally with high-performance compute, systems, vehicle engineering, autonomy, and suppliers as the end-to-end Radar owner and domain expert to architect and define an optimal sub-system.
  • Use your top-notch development expertise to inspire others to develop better practices and principles.
  • Mentor junior researchers by providing guidance on research projects and design document reviews.

What We're Looking For

  • Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, Electrical Engineering or a related field.
  • Deep understanding of Radar hardware, Radar DSP, Radar machine learning, and Radar testing/performance that informs optimal machine learning performance.
  • Experience developing low-level data pipelines to enable industry-leading machine learning performance.
  • Understanding of computer architecture principles and how data pipelines and machine learning algorithms map onto hardware.
  • In-depth understanding of common machine learning and deep learning algorithms (e.g. for classification, regression, and clustering).
  • Experience designing, training, and analyzing neural networks for at least one of the following applications: object detection, image segmentation, sensor fusion, multitask learning, motion prediction, and/or tracking.
  • Significant experience with software engineering principles including software design, source control management, build processes, code reviews, testing methods.
  • Fluency in Python, including standard scientific computing libraries and Python bindings development experience.
  • Experience with PyTorch or other deep learning frameworks.
  • Experience defining data collection, data curation, and working with large datasets.
  • Leadership and mentoring experience.

Bonus Points (Not Required)

  • Proven track record of publications in relevant conferences.
  • Strong programming skills in C++ and/or CUDA programming.
  • Experience with physical simulation of Radar and other sensors.

Why You Should Join Us

  • Join a world-class team of engineers including inventors of nuScenes, PointPillars, PointPainting, ADCNet, and AAETR.
  • Lead an end-to-end Imaging Radar & machine learning development to set a new performance benchmark for what is possible.
  • Design and implement the system the right way.
  • Speaking and publication opportunities are encouraged and supported.

Skills

Radar Systems
Hardware Design
Data Processing
Machine Learning
Deep Neural Networks
Deep Learning
Deep Learning Codebase
Autonomous Vehicles
Sensor Fusion
Research
Development
Engineering
High Performance Compute
Systems Engineering
Vehicle Engineering
Autonomy Engineering
Electrical Engineering
Computer Science
Applied Mathematics
Statistics
Physics

Motional

Develops fully driverless robotaxis for urban transport

About Motional

Motional develops fully driverless vehicles, specifically robotaxis, aimed at transforming urban transportation. Their all-electric robotaxis are designed to navigate complex city environments safely and efficiently. Motional partners with ride-hailing and delivery services, providing them with advanced autonomous vehicle technology to enhance their operations and reduce costs. A unique aspect of Motional's service is its Command Center, which allows for real-time tracking of each robotaxi, enabling human agents to monitor performance and ensure passenger safety. Unlike many competitors, Motional focuses on integrating its vehicles into existing mobility networks, making driverless technology accessible and reliable. The company's goal is to make autonomous vehicles a safe and integral part of urban transportation.

Boston, MassachusettsHeadquarters
2020Year Founded
$5,000MTotal Funding
GROWTH_EQUITY_NON_VCCompany Stage
Robotics & Automation, Automotive & TransportationIndustries
1,001-5,000Employees

Benefits

401K: 401K with up to 7.5% match
time Off: Unlimited sick and vacation days
Transportation: Commuter and fitness benefits
Healthcare: 3 plan options to support diverse needs
IVF: Fertility assistance

Risks

Motional laid off 550 employees, indicating financial and operational challenges.
Aptiv reduced its stake in Motional, impacting operational capabilities.
Delays in autonomous vehicle deployment to 2026 could hinder market entry plans.

Differentiation

Motional offers a state-of-the-art Command Center for real-time robotaxi tracking.
The company focuses on all-electric, driverless robotaxis for urban environments.
Motional partners with ride-hailing services to integrate autonomous vehicles into their operations.

Upsides

Motional raised $475 million from Hyundai, indicating strong financial backing.
Partnerships with Uber and Shake Shack expand Motional's market reach in delivery services.
Increased investment in robotics highlights potential funding opportunities for Motional.

Land your dream remote job 3x faster with AI