Senior Deep Learning / Machine Learning Engineer, Motion Planning

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 deep learning expert to drive the research and deployment of the next generation of deep learning models for Autonomous driving. As an expert in machine learning, you will be working with the Motion Planning Team on developing a machine learning first approach to motion planning that combines the latest findings in deep learning, reinforcement learning, imitation learning, motion planning, and robotics. The ideal candidate will have published some deep learning research in top-tier conferences such as NeurIPs or CVPR, built and deployed real-world deep learning products, and worked 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
• Develop state-of-the-art methods that leverage imitation learning, deep reinforcement learning, and large-scale data to develop a machine learning first approach to motion planning, taking into account many factors such as scalability, inference speed, and generalization power.
• Train neural networks on massive volumes of data, and build the necessary metrics and introspection tools to enable rapid iteration
• Be a champion of the scientific method and critical thinking in inventing state-of-the-art deep learning solutions but is also a leader in applying rigorous engineering practices during validation and deployment
• Stay up to date with the latest research and trends in the fields and apply new state-of-the-art solutions.
• Collaborate closely with teams such as Perception, Simulation, Infrastructure, Tooling to drive unified solutions
• Advance the state-of-the-art and represent Level 5 at top-tier conferences (e.g. CVPR, NeurIPs, ICCV, CoRL, ICRA)

Experience:

• Advanced degree (Ph.D. preferred) in Machine Learning, Robotics, CS (or other related fields), or other quantitative fields or relevant work experience. 
• Minimum 5 years experience preferred
• Experience with learning-based planning approaches like imitation learning, reinforcement learning and state-of-the-art techniques for sequential modelling like Transformer architectures, and state-of-the-art vector/point-based input representations. 
• Programming experience implementing cutting-edge deep learned ML solutions using PyTorch / Tensorflow and distributed training. 
• Understanding of ML workflow: preparing and sampling the data, implementing and training ML models, evaluating results, running ablation studies, deploying inference on different platforms
• (Nice to Have) Experience with robot motion planning techniques like trajectory optimization, sampling-based planning, model predictive control, etc or self-driving problems (Perception, Prediction, Mapping, Localization, Planning, Simulation)
• (Nice to Have) Experience with temporal/sequential modeling and/or reinforcement learning.
• (Nice to Have) Experience targeting power-efficient, edge-compute architectures