Senior Machine Learning Engineer

On Behaviors , you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality and create positive social impact. Our team works on the tech stack responsible for understanding highly complex driving scenes and generating safe, comfortable driving trajectories for our robotaxi using the latest deep neural networks. We are looking for engineers who are passionate about Level 5 autonomous driving, excited by intellectual challenges, and interested in pursuing career growth with a fast growing company. What You’ll Be Doing: You will be directly responsible for training, evaluation, and deployment of our ML-based scene understanding, behavior prediction, and planning models. Day to day responsibilities include: Designing and executing high value experiments based on collaborative input from other machine learning engineers Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities Timely release of major model updates, including analysis of both off-line and on-road evaluation data Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation What We’re Looking For: In-depth understanding of common Machine Learning and Deep Learning algorithms Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and testing methods Experience with PyTorch or other python-based deep learning frameworks Experience working with large data sets and deriving insights from data Experience mentoring and collaborating with others Education Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience Bonus Points Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.) PhD in machine learning, computer vision, or robotics vision Experience working on autonomous vehicles or related fields Experience in deploying models into real-world environments Strong programming skills in C++ and/or CUDA programming This opportunity can support remote work within the United States, with occasional travel. Working Conditions 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 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 $146,000 — $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 and follow us on Twitter , LinkedIn , Instagram 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.