MLOps Engineer, Perception

TEAMWoven 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.