Woven · London
Data & AIProduct & TechnologyHybridEmployeeposted 2w ago
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 seeking an experienced, technical, and hands-on Autonomy Data Manager to grow and lead a talented team composed of Data Scientists, Data Engineers and ML Ops Engineers, working in the Autonomy team to deliver data driven Planning and Perception solutions. You will lead the team to drive the creation and deployment of sophisticated data models and algorithms to resolve business challenges for the Autonomy team. You lead through your expertise in data, deep learning and software engineering. You provide technical guidance to the team by combining modern data approaches with safety standards while also considering cost efficient options.. 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.
Define the team's short-term and long-term technical direction while collaborating on broader, cross-functional strategic initiatives across Perception, Planning, Simulation, Infrastructure, and Tooling.
Initiate and influence cross-functional teams towards common data development goals and unified solutions.
Support the data roadmap for the program and connect your team’s technical roadmap by focusing on actionable data strategy approaches from data collect strategies, to data curation, labelling , sampling, evaluation, with a goal of leveraging the large amounts of Toyota’s market fleet data to directly improve machine learning model performance across the End-to-End Autonomy Data pipeline.
Lead initiative execution by defining efficient processes, mitigating technical risks, and anticipate long-term strategic improvements within the team and across the program.
Enable and develop each team member to be more effective through coaching and leading by example providing high-quality algorithms, carefully thought out design reviews, and delivering rigorous initiative reports.
Collaborate and provide technical guidance in the design, development, deployment, optimization, and evaluation of state‑of‑the‑art data algorithms, data efficiency and pipelines to enable ML model performance with a focus on iteration speed, scalability and overall cost efficiency.
Drive a culture of rigorous statistical evaluation to measure, validate and implement evaluation frameworks that support ML model development and improved system behavior.
Drive organizational metrics towards performance, safety, and quality.
Work in a high-velocity environment, employ agile development practices, and collaborate in a globally distributed department (US, Japan, UK).
Masters or PhD degree in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, or related quantitative fields, or equivalent industry experience
3+ years of experience managing engineering teams, with a focus on technical leadership, team development, and delivering high-impact projects in the automotive industry.
8+ years of experience covering data science, data sampling and curation, machine learning workflows, pre-processing, model training, ablation studies, evaluation, deployment, and inference optimization.
Experience with rigorous data science for applications leveraging large scale data sources and highly efficient pipelines
Experience working with large-scale robotics datasets, temporal data and/or sequential modeling
Excellent communication skills with the ability to communicate concepts clearly and precisely
Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure)
Experience as a Data Architect or Senior Manager
Proven track record of deploying ML models at scale in self-driving products, self-driving challenges, or related fields
Experience with production data pipelines or Safety & Quality processes for safety-critical applications
Hands-on experience in the following:
Analyze huge (e.g. peta byte) scale database;
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