Woven by Toyota
Staff Software Engineer, ML Platform
Woven by Toyota, Palo Alto, California, United States, 94306
Woven by Toyota is the mobility technology subsidiary of Toyota Motor Corporation. Our mission is to deliver safe, intelligent, human-centered mobility for all. Through our Arene mobility software platform, safety-first automated driving technology and Toyota Woven City - our test course for advanced mobility - we're bringing greater freedom, safety and happiness to people and society.
Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. We leverage these complementary strengths to amplify the capabilities of drivers, foster happiness, and elevate well-being.
TEAM
We work in the ML training and deployment ecosystem, you will be embedded within the Automated Driving & ADAS team and work directly with Autonomy ML engineers to accelerate development and deployment of ML models. Your work will support improving the quality of our production models deployed on cars and develop tools to support training and deployment of ML models on large scale data. You will work with a set of large-scale and interconnected tools, and help in improving scalability, efficiency, and utility of all aspects of the ML ops ecosystem. You will operate across ML Platform, production model owners, research, and cloud infrastructure to deliver efficient fast tools for integration, testing, and deployment of those models. This role is hybrid and will report to the Engineering Manager located in Palo Alto, CA.
RESPONSIBILITIES:
Develop and integrate SOTA methods for efficient, large-scale training of ML models and support multi-platform deployment including automotive-grade edge compute devices Architect and develop tools for ML model evaluation and end-to-end validation to help ML engineers assess impact of their changes to downstream customers and modules Improve the utility of our vehicle data by building and improving the infrastructure for data sampling, data curation and data representation; improve versatility of our ML data format to support data reuse across models Operate cross-functionally and identify bottlenecks such as latency hot spots during training and deployment of ML models, while generalizing needed tools Scale our architecture while taking advantage of heterogeneous clusters to maximize resource efficiency QUALIFICATIONS:
Experience in building large-scale data intensive distributed model training and evaluation ecosystems and pipelines Experience in the full ML Ops cycle covering data cleansing, data sampling, data curation, training, testing, and deployment in the cloud and on edge compute platforms Expert Python practitioner and familiarity with PyTorch Familiarity with containerization and workflow orchestration systems, e.g. Docker, Kubernetes, Airflow, Flyte Familiarity with C++
For California: The base pay for this position ranges from $161,000 - 264,500 a year
Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.
WHAT WE OFFER
We are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility.
• Excellent health, wellness, dental and vision coverage
• A rewarding 401k program
• Flexible vacation policy
• Family planning and care benefits
Our Commitment
• We are an equal opportunity employer and value diversity.
• Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.
Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. We leverage these complementary strengths to amplify the capabilities of drivers, foster happiness, and elevate well-being.
TEAM
We work in the ML training and deployment ecosystem, you will be embedded within the Automated Driving & ADAS team and work directly with Autonomy ML engineers to accelerate development and deployment of ML models. Your work will support improving the quality of our production models deployed on cars and develop tools to support training and deployment of ML models on large scale data. You will work with a set of large-scale and interconnected tools, and help in improving scalability, efficiency, and utility of all aspects of the ML ops ecosystem. You will operate across ML Platform, production model owners, research, and cloud infrastructure to deliver efficient fast tools for integration, testing, and deployment of those models. This role is hybrid and will report to the Engineering Manager located in Palo Alto, CA.
RESPONSIBILITIES:
Develop and integrate SOTA methods for efficient, large-scale training of ML models and support multi-platform deployment including automotive-grade edge compute devices Architect and develop tools for ML model evaluation and end-to-end validation to help ML engineers assess impact of their changes to downstream customers and modules Improve the utility of our vehicle data by building and improving the infrastructure for data sampling, data curation and data representation; improve versatility of our ML data format to support data reuse across models Operate cross-functionally and identify bottlenecks such as latency hot spots during training and deployment of ML models, while generalizing needed tools Scale our architecture while taking advantage of heterogeneous clusters to maximize resource efficiency QUALIFICATIONS:
Experience in building large-scale data intensive distributed model training and evaluation ecosystems and pipelines Experience in the full ML Ops cycle covering data cleansing, data sampling, data curation, training, testing, and deployment in the cloud and on edge compute platforms Expert Python practitioner and familiarity with PyTorch Familiarity with containerization and workflow orchestration systems, e.g. Docker, Kubernetes, Airflow, Flyte Familiarity with C++
For California: The base pay for this position ranges from $161,000 - 264,500 a year
Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.
WHAT WE OFFER
We are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility.
• Excellent health, wellness, dental and vision coverage
• A rewarding 401k program
• Flexible vacation policy
• Family planning and care benefits
Our Commitment
• We are an equal opportunity employer and value diversity.
• Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.