TEAM
Woven by Toyota develops, implements, and scales human-centered automated driving solutions for personal and commercial use. Our team is responsible for developing perception technologies and its production software for the AD/ADAS system. To realize a fully reliable and highly functional system, we are tackling complex real-world problems utilizing large scale data, machine learning algorithms, and a variety of perception technologies.
WHO ARE WE LOOKING FOR?
The ideal candidate is self-motivated to find solutions to complex real-world problems, and makes an impact while contributing to a cross-functional team. You will combine cutting-edge technologies with robust safety standards while also considering cost efficiency. Also, you have patience to tackle the processes required for production development and approach them by asking “What can I do for you?” with a “Giver” mindset.
RESPONSIBILITIES
Address large scale challenges in the machine learning workflow, especially around data pipeline, continuous integration, evaluation, and deployment on an embedded system
Architect and implement scalable MLOps and DevOps pipelines in the cloud with CI/CD best practices
Maintain ML training environment such as host configuration, docker image, training code, and dataset
Manipulate high-volume, high-dimensional structured data from driving logs for training and evaluating the perception stack
Develop visualization, analytics, and monitoring for the perception stack
Help ensure surrounding elements for ML systems are implemented to a high security standard
MINIMUM QUALIFICATIONS
BS/MS in Computer Science or the equivalent in experience with evidence of exceptional ability
3+ years of experience with software development especially in MLOps, DevOps, or related areas
Professional experience with building software on cloud platforms
Professional experience with ML infrastructure, CI/CD, and visualization tools
Business-level English
NICE TO HAVES
Knowledge of deep learning models and techniques, especially in computer vision
Experience with DevOps tools (e.g. GitHub Actions), MLOps tools (e.g. SageMaker, Kubeflow, Flyte), and infrastructure management tools (e.g. k8s, Terraform)
Experience with databases (Relational, Key-value, Document), data warehouse (e.g. Snowflake, BigQuery) and data transformation (e.g. Spark, Ray)
Knowledge or strong interest in application security and infrastructure security
If you are located outside of Japan we will set up an interview over Google Hangout Meet.
