Lead Onboard Behavior ML - Strategy & Team Manager

Zoox; Foster City (CA); On-site; USD 277,000 - 349,000; Full time

Benefits offered by this job

Paid time off

Unpaid time off

Zoox Stock Appreciation Rights

Amazon RSUs

Health insurance

Long-term care insurance

Long-term and short-term disability 보험

Life insurance

Job summary

Zoox is seeking a leader for the Onboard Behavior Model Architecture team to advance deep learning models that drive safe, comfortable autonomous driving. You will collaborate with multiple partner teams to identify opportunities for model improvements and to set the short- and long-term technical direction.

The role emphasizes training models at scale, providing technical guidance, monitoring KPIs, and ensuring resources are allocated effectively so projects succeed.

Qualifications

• Expertise with reinforcement learning and ML for planning, LLMs, VLAs/VLMs, or recommendation systems.
• Strong programming and algorithm design skills with solid mathematics.
• MS or PhD in computer science or a related field.
• 5+ years of production ML experience, with at least 3 years in leadership.

Responsibilities

• Lead, mentor, and grow a team of individual contributors while fostering innovation.
• Develop and organize the strategy for onboard behavior ML models and driving plans.
• Provide technical guidance for training at scale and coordinate efficient inference.
• Monitor KPIs and drive continuous improvement across work packages.
• Allocate resources and ensure teams have tools and support to succeed.

Skills

Reinforcement Learning

Machine Learning

Planning

LLMs

VLAs/VLMs

Recommendation systems

Education

MS or PhD in Computer Science or related field

Job description

Zoox is seeking a leader for the Onboard Behavior Model Architecture team to advance deep learning models that drive safe, comfortable autonomous driving. You will collaborate with multiple partner teams to identify opportunities for model improvements and to set the short- and long-term technical direction.

The role emphasizes training models at scale, providing technical guidance, monitoring KPIs, and ensuring resources are allocated effectively so projects succeed.