Woven by Toyota is enabling Toyota's transformation into a mobility company by developing autonomous driving and advanced driver assist technologies, a software development platform for software-defined vehicles, a test course for mobility, and the digital infrastructure powering these initiatives. The company aims to solve challenges in AI, Robotics, and Advanced Driving, including analyzing large datasets, optimizing performance, and deploying scalable ML pipelines to millions of Toyota customer vehicles.
Requirements
- 10+ years of experience with data structures, algorithms, design patterns, and software engineering best practices.
- 4+ years of experience with UNIX-based systems (Linux or similar), Python, and PyTorch/Tensorflow.
- 4+ years of experience in the full MLOps cycle covering data cleansing, data sampling, data curation, pre-processing, training, testing, evaluation, deployment, inference optimization and deployment in the cloud and on edge compute platforms.
- Experience with scaling ML training and fixing the typical issues found at large scale.
- Experience with Docker and CI systems such as GitHub Actions.
- 4+ years of experience with Apache Spark, Airflow, Flyte, Flink, Ray, or similar ML pipelines technologies.
- 4+ years using modern systems programming languages (e.g., Rust and/or C++) and a modern build system (preferably Bazel), and systems-level debugging knowledge, in a professional environment.
Responsibilities
- Design, build, maintain, optimize and support the ML Platform’s systems and tools for perception, prediction, and planner development, allowing numerous ML engineers to effectively & efficiently iterate on dataset curation, ML modeling, training, evaluation and deployment of ML models into our functionally safe AD/ADAS stack, shipped in millions of Toyota vehicles.
- Develop user-friendly tooling, frameworks and libraries to support the overall ML engineering effort, from ML modeling, to tracking performance metrics and introspecting failure modes.
- Build and maintain efficient data curation, cloud training and evaluation pipelines.
- Develop and review code with other ML and ML Platform engineers to facilitate rapid incremental improvements.
- Optimize the current processes, tooling and supporting infrastructure to accelerate the overall ML engineering effort, and contribute to the long term strategy for several of our systems and products.
- Work in a high-velocity environment and employ agile development practices.
- Work cross functionally to align on the target architecture of our systems and optimize processes & systems globally.
Other
- Work in a hybrid workspace, with the requirement to be present in our Palo Alto, CA office three days per week.
- Drive best engineering practices across the organisation
- Business-level proficiency in English, able to write technical documents (e.g. for software documentation).
- Experience working in a fast-paced environment, collaborating across teams and disciplines.
- We are looking for individuals who exhibit a "giver" mindset, consistently seeking opportunities to assist their colleagues while maintaining a strong focus on delivering solutions to production.
