Level 5, part of Woven Planet, is developing self-driving technology using a machine-learned approach to create safe mobility for everyone. Our goal is to build level 4 autonomous vehicles to improve personal transportation on a global scale. Woven Planet is a software-first subsidiary of Toyota whose vision is to create mobility of people, goods, and information that everyone can enjoy and trust.
As part of Woven Planet, Level 5 has the backing of one of the world’s largest automakers, the talent to deliver on our goal, and the opportunity for near-term product impact and revenue—a combination rarely seen in the AV industry.
Level 5 is looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology. We’ve built a diverse and talented group of software and hardware engineers, and each has the opportunity to make a meaningful impact on our self-driving stack.
Our team of more than 300 works in brand new garages and labs in Palo Alto, tests AVs at our dedicated test track in the Silicon Valley, and explores the AV industry’s most compelling research problems at our office in London. With support from more than 800 Woven Planet colleagues in Tokyo, Level 5’s work to improve the future of mobility spans the globe. And we’re moving fast — in Level 5’s first 18 months, we launched an employee pilot, and are now testing our fourth generation vehicle platform in San Francisco. Learn more at level-5.global.
As an expert in machine learning and distributed systems, you will work directly with our autonomy and research teams to improve our machine learning framework at scale. You will help scale both the algorithms and infrastructure for distributed training and inference to unprecedented levels, allowing users to build models using petabytes of data (collected from a large fleet of vehicles), thousands of nodes, and huge capacity. At the same time, you will help evaluate these models using massively parallel metrics and simulation and deploy them to compute-constrained devices. You will work in a fast paced environment and interact with a wide variety of teams ranging from ML researchers to cloud engineers. The ideal candidate should be well versed in the fundamentals of deep learning and distributed systems. Your work will directly contribute to our team’s ability to build and deploy state of the art deep learning systems for autonomous driving.
- Build and scale our PyTorch based machine learning system that powers all deep learning systems on the AV and on the cloud at Level 5
- Be a champion for model and data code quality and maintain a high standard when shipping new features
- Scaling deep learning algorithms to 100s of GPUs and massive data sets efficiently
- Tackle unsolved problems ML algorithms at scale such as optimization in large scale distributed training, multitask learning, domain adaptation, neural architecture search, and intelligent sampling.
- Dive deep into unknown areas in machine learning, high-performance computing, and cloud infrastructure
- Focus on delivering impact to our customers
- Bachelors in Computer Science or a related field
- Experience in building large scale backend systems or working with ML infrastructure
- Experience working with Python and C++
- Detailed understanding of the ML lifecycle: data preprocessing, modelling, training, evaluation, and edge/cloud inference
- Experience working with cloud infrastructure such as AWS, GCP, and Kubernetes
- (Nice to have) Background in high-performance computing (HPC), optimization, or simulation
- (Nice to have) Familiarity with parallel programming libraries such as MPI
- (Nice to have) Have one or more high profile publications in ML
・We are an equal opportunity employer and value diversity.
・We pledge that any information we receive from candidates will be used ONLY for the purpose of hiring assessment.