Machine Learning Software Engineer, Motion Planning Compute

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Woven Planet is building the safest mobility in the world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all.

For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today. Now, we are looking to the next 100 years and to extending that dream for a better life for all people. At Woven Planet we strive to build a safer, happier, more sustainable world.

Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. The complementary strengths enable us to optimize safety, advance clean energy, elevate well-being, and improve how people live, work, and play. We envision a human-centered future where world-class technology solutions expand global access to mobility, amplify the capabilities of drivers, and empower humanity to thrive.

About the Organization

Woven Planet is developing automated driving technology using a data-driven approach. We’re building products at autonomy levels 2-4 to drive both near- and long-term improvements to mobility for all. Woven Planet has the backing of one of the world’s largest automakers, the talent to deliver on our goal, and a built in path to product and revenue—a combination rarely seen in the mobility industry. We’re looking for doers and creative problem solvers with a passion for improving lives.

Each member of our diverse and talented group of software and hardware engineers has the opportunity to make a meaningful impact on our technology and products. Our growing team works in brand new garages and labs in Palo Alto, tests AVs at our dedicated test track in Silicon Valley, and explores the industry’s most compelling research problems at our office in London. With support from our Woven Planet colleagues in Tokyo, our work to improve the future of mobility spans the globe.

You will be interacting on a daily basis with software engineers, machine learning specialists, and researchers to tackle some of the most challenging problems in AI and robotics. We work on a diverse set of problems ranging from solving motion planning problems in challenging traffic situations, to minimizing latency on hardware accelerators, to designing novel neural network architectures.

The team is looking for a machine learning software engineer that drives the deployment of our deep learning models to the vehicle software and hardware stack. As an expert, you work with the Motion Planning Team to adapt our neural networks to run efficiently on our compute platforms. The ideal candidate will have experience in specializing deep learning networks and optimizing inference to the specifics of the target deployment compute architectures, experience in building and deploying real-world deep learning products, and experience working in a fast-paced environment along with other highly talented engineers. We recognize the unique capabilities each team member can bring, though and encourage applicants to reach out even if they do not match all of the characteristics described below. 

 Responsibilities:

• Work in a small, high-velocity team of engineers and researchers
• Work closely with researchers and engineers in the motion planning team to deliver optimal execution of the data-driven motion planning algorithms on the target edge compute platform.
• Develop tools to profile and benchmark performance bottlenecks in data processing or inference pipeline on the target compute, recommend and implement optimized solutions.
• Mentor the team and create tools/pipelines for developers to experiment with approaches that are compatible and efficient with respect to the target platform.
• Collaborate closely with teams such as Autonomy Compute, Perception and Infrastructure to leverage and improve generalizable solutions across autonomy.

Experience:

• BS/MS in Computer Science, Machine Learning, or equivalent practical experience