
About Motional
Driving the future of autonomous mobility safely
Key Highlights
- Partnership with Lyft for autonomous ride-hailing services
- Extensive testing in Las Vegas and Boston
- Headquartered in Boston, Massachusetts
- Over 1,000 employees dedicated to autonomous technology
Motional, headquartered in Boston, Massachusetts, is a leader in autonomous vehicle technology, specializing in driverless cars and mobility solutions. The company has partnered with major players like Lyft and has conducted extensive testing in cities such as Las Vegas and Boston. With over 1,000 e...
🎁 Benefits
Motional offers competitive salaries, equity options, generous PTO, comprehensive health benefits, and a flexible remote work policy to support work-l...
🌟 Culture
Motional fosters a culture of innovation and safety, emphasizing collaboration among engineers and researchers to push the boundaries of autonomous te...
Skills & Technologies
Overview
Motional is seeking a Senior Machine Learning Engineer to work on scene understanding and behavior prediction for self-driving vehicles. You'll collaborate with top ML engineers and utilize technologies like TensorFlow and Keras. This role requires in-depth knowledge of machine learning algorithms and experience in model training and deployment.
Job Description
Who you are
You have a strong background in machine learning and deep learning algorithms, with a focus on practical applications in autonomous driving. Your experience includes designing and executing experiments that yield high-value insights, and you are comfortable collaborating with other engineers to enhance model performance. You are familiar with the latest trends in the industry and are eager to propose innovative architectures based on current research. Your coding skills are top-notch, and you maintain a high-quality codebase for training and evaluation processes.
You are passionate about Level 5 autonomous driving and understand the complexities involved in creating safe and efficient driving trajectories. You thrive on intellectual challenges and are committed to continuous learning and career growth within a fast-paced environment. Your ability to analyze both offline and on-road evaluation data is crucial for timely model updates, ensuring that the technology remains at the forefront of the industry.
Desirable
Experience with large datasets and the ability to implement metrics that evaluate model performance across various scenarios is a plus. Familiarity with cloud computing platforms and tools for deploying machine learning models will enhance your contributions to the team.
What you'll do
In this role, you will be responsible for the training, evaluation, and deployment of machine learning models that focus on scene understanding and behavior prediction for our robotaxi technology. You will design and execute experiments that leverage collaborative input from your peers, ensuring that the models you develop are robust and effective in real-world scenarios. Your day-to-day responsibilities will include maintaining a high-quality training and evaluation codebase, which is essential for dataset generation and performance evaluation.
You will stay updated with the latest advancements in machine learning and propose new architectures and network designs based on published literature. Your contributions will directly impact the safety and comfort of our self-driving vehicles, making a significant difference in the future of transportation. You will work closely with a team of world-class ML engineers and research scientists, fostering an environment of innovation and excellence.
What we offer
Motional provides a collaborative and inclusive work environment where you can grow your skills and advance your career. We celebrate diversity and are committed to creating a workplace that reflects the communities we serve. You will have the opportunity to work on cutting-edge technology that aims to revolutionize the transportation industry, contributing to a positive social impact. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.
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