Senior Machine Learning Engineer: Radar Camera Fusion

Mission Summary:

On our Autonomy Sensor team, you have the opportunity to build state-of-the-art sensor suites and develop end to end ML/DL based processing and fusion pipelines to further enable a wide spectrum of downstream tasks (perception, prediction, localization, etc). in our AV’s SW stack for our next generation L4/5 autonomous vehicles. As an ML engineer, you will drive the design, implementation, training, evaluation and deployment of machine learning models that process and fuse raw data from radar, camera and lidar sensors to create a data product for a wide spectrum of downstream tasks. An ideal candidate will work on the R&D of a learned radar imaging model, ML imaging processing and feature extraction model and/or multi-modality sensor fusion model architectures that are scalable to a wide spectrum of sensors and downstream tasks.

What you'll be doing: 

• Lead the development of ML models, training and evaluation pipeline for radar and camera data processing and fusion in our next generation AV system
• Collaborate with an interdisciplinary team of ML/algorithm, sensor, and software experts within perception, platform infrastructure and ML infrastructure
• Help develop ML focused metrics and define requirements for our next generation sensor suite
• Participate in code reviews on code quality, correctness and efficiency
• Prepare real or synthesize dataset with different radar fusion models for ML training
• Communicate the results of these studies clearly to engineering team

What we're looking for: 

• MS in computer science, engineering, or applied math with 5+ years practical experience in machine learning, sensing and perception in automotive systems
• Experience developing, training, evaluating machine learning models with large data sets on a scalable system and deploying models on our autonomous vehicle platform
• Hands-on experience with raw data from sensors such as Radar, camera, thermal and lidar sensors as well as in-depth understanding of their working principles
• Experience with PyTorch or other deep learning frameworks
• Fluent in Python
• Ability to communicate across multiple teams, researchers, and engineers

Bonus points: 

• Background/understanding of fundamental radar principles and radar processing techniques
• Experience with development of customized CUDA kernel is desired
• Fluency in C++

Why you should join us: 

Our team is commercializing a world-class driverless system. The Motional team is behind some of the industry’s largest leaps forward in the last decade, 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 most-established public robotaxi fleet. Strategically formed by Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives.

We value diversity, equity, and inclusion and provide a supportive work environment that prioritizes collaboration, communication, and creativity. Our team members are committed to delivering high-quality results that make a real difference in the world. If you are passionate about the future of autonomous vehicles and want to work with a team of talented and motivated professionals, we encourage you to apply to join our Autonomy Sensors team.  Additionally, we offer excellent benefits to include generous medical plans, wellness benefits, unlimited PTO, 401k and equity, to name a few.

Work environment: 

The Motional global headquarters are located at 100 Northern Avenue in Boston, MA. Nestled in the bustling Seaport district with sweeping views of Boston Harbor and downtown Boston, the offices are located close to major transit lines and a quick walk to various restaurants and popular attractions.  This position can support remote work within the United States only. 

• While performing the duties of this job, the employee is frequently required to convey and detect communication
• The employee occasionally required to remain stationary at times for up to 50% of working time, move in designated working areas; & operate and use office equipment
• The employee may occasionally move up to 50 pounds