Senior Data Scientist, AD/ADAS

Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.

Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.

TEAM At Woven by Toyota, we tackle Autonomy challenges at the intersection of AI, Robotics, and Advanced Driving. We develop advanced Perception and Planning technologies, and their production software for multiple AD/ADAS systems. To deliver reliable data-driven technologies to millions of Toyota vehicles, we are solving complex real-world problems using large-scale data, machine learning, and state-of-the-art architectures for Perception, Prediction, and Motion Planning.

WHO ARE WE LOOKING FOR? The team is looking for a strong Data Scientist to drive the creation and deployment of sophisticated data models and algorithms to resolve business challenges for the Autonomy team. You will combine modern data approaches with safety standards while also considering cost efficient options. You will be an expert in deep learning and software engineering. Furthermore, you are proactive towards handling the processes required for production development and approach them by asking "What can I do for you?" with a "Giver" mindset.

Develop data strategies on how to collect, sample, label, handle, and leverage large amounts of data from Toyota’s market fleet, test vehicles, and simulators, to directly improve machine learning model performance across perception and planning stacks Lead data-related activities across the autonomy team (perception, planning, product evaluation, etc), and across the company in collaboration with the Toyota group, by collaborating closely with stakeholders from multiple teams in different time-zones Analyze large-scale data and identify its characteristics to propose technical solutions for data curation, model improvement and performance evaluation techniques Develop evaluation frameworks and metrics to assess planner performance, identifying edge cases and high-value scenarios to improve system behavior. Design and improve the scalable data pipelines and automation for machine learning and performance evaluation Enhance the overall team capabilities in data science by initiating and leading initiatives across the Autonomy teams and mentor team members.

Masters or PhD degree in a quantitative field related to Science and Engineering. 5+ years experience in following industries or research areas: AD/ADAS, Robotics, Computer Vision, or Behavioral Planning. 3+ years experience in data science or related areas, including theoretical aspects of data science like machine learning (deep learning, statistical analysis, A/B testing, and mathematical modeling) Experience in building machine learning algorithms and infrastructure, such as: data pre- and post-processing, sampling and curation, ablation studies, evaluation Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) database; and iii) cloud platform services (AWS, GCP, Azure)

5+ years experience in data science or related areas 2+ years tech lead or management experience in data science or related areas for business applications, such as production, commercial service or public service development Hands-on experience in the following: Analyze huge (e.g. peta byte) scale database Experience with temporal/sequential and/or spatial data Develop perception-related technologies, such as camera image processing, computer vision, machine learning, or deep learning Design data annotation rules for machine learning Build or manage infrastructure, such as Docker, Kubernetes, Jenkins, GitHub Actions Behavior prediction, imitation learning, reinforcement learning, or end-to-end models. Japanese language skills

laptop-ats-crawler v3