Lead Behavior Engineer - Machine Learning

Woven by Toyota; Palo Alto (CA); On-site; USD 189,000 - 311,000; Full time

Job summary

Woven by Toyota is seeking a Lead Behavior Engineer - ML to accelerate machine learning solutions for vehicle behavior. This role combines technical strategy with hands-on execution and mentorship in an innovative environment aimed at redefining mobility through advanced driving technologies.

Benefits

Excellent health, wellness, dental, and vision coverage

A rewarding 401k program

Flexible vacation policy

Family planning and care benefits

Qualifications

• 10+ years of professional experience with machine learning applications.
• Ability to write code in C++ and Python.
• Strong practical understanding of real-time system development.

Responsibilities

• Drive a multi-year technical strategy for accelerating data-driven and deep learning approaches.
• Lead the execution of projects by defining efficient engineering processes.
• Collaborate with cross-functional teams while influencing technical decisions.

Skills

Machine Learning Algorithms

Model Architecture

Data Curation

Supervised Learning

Unsupervised Learning

Communication Skills

Education

MS or PhD in Machine Learning, Engineering or similar

Job description

Woven by Toyotais enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.

Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.

TEAM

Woven by Toyota's AD/ADAS organization is developing the core algorithms for safe and robust driving of complex and uncertain real-world environments. Our teams are contributing to next generation autonomy and ADAS active safety systems through core algorithms, data-driven approaches, and efficient architectures. The Behavior Department within AD/ADAS is responsible for accelerating ML and AI technology to deliver state-of-the-art and safe vehicle behaviors. Working across the spectrum of active safety and L2-L4 autonomy, the team delivers core technology in the areas of perception, planning, control, and HMI towards production targets with Toyota.

WHO ARE WE LOOKING FOR?

The Lead Behavior Engineer - ML will work hand-in-hand with the Behavior Department Head to drive the roadmap, architecture, metrics, and technical strategy to accelerate machine learning solutions related to vehicle behavior. This role requires a system thinker with technical depth in machine learning approaches to complex systems. The applicant should have a strong background in ML algorithms, model architecture, end-to-end strategies, ML frameworks, data curation, and supervised and undervised metrics. The role requires strong communication skills, an aptitude for mentoring junior tech leads, and a split between independent technical execution and cross-organizational problem solving.

RESPONSIBILITIES

• Drive a multi-year technical strategy for accelerating data-driven and deep learning approaches to deploy Behavior software components for AD/ADAS applications, ensuring scalable, high-performance solutions while maintaining best practices for software development and system design.
• Lead the execution of projects by defining efficient engineering processes, mitigating technical risks, and advocating for architectural improvements that enhance system reliability and scalability.
• Collaborate with cross-functional teams such as Data, Perception, Developer Ecosystem, and Product Delivery while influencing technical decisions across the organization to drive innovation, ensure seamless system integration, and improve overall engineering efficiency.
• Develop state-of-the-art models to deliver desired driving behaviors in various driving scenarios.
• Increase speed of the component- and system-level model iteration while maintaining cost efficiency
• Incorporate data-driven approaches to improve system performance and unlock new capabilities for safety.
• Maintain the functional architecture design and lead review of technical designs
• Drive organizational metrics towards performance, safety, and quality
• Maintain external presence of the department through papers, patents, and presentations
• Assess and mitigate risk to the technical program
• Act in partnership with other Lead Engineers in AD/ADAS to solve high impact cross-functional issues
• Mentor and support engineers, fostering growth through code reviews, knowledge sharing, and collaboration with cross-functional teams to align technical solutions with business goals.
• Design reusable software components as part of an integrated system.
• Understand and fulfill the software practices that produce maintainable code, including simulation, continuous integration, code review, HIL testing, and in-vehicle testing.
• Build component and system level validation strategies that are leveraged to resolve complex interactions between components, increase performance, and evaluate design tradeoffs related to data-driven practices

MINIMUM QUALIFICATIONS

• 10+ years of professional experience with machine learning applications or applied science
• MS or PHD in Machine Learning, Mechanical, Electrical, Computer, Aerospace Engineering, or similar
• Deep experience with ML system design and verification over a variety of approaches, including supervised/unsupervised learning, reinforcement learning, diffusion policy
• Strong R&D potential in algorithm design, data-driven approaches to safety, and large-scale, complex systems architecture, and requirements-driven development
• Experience with utilizing deep learning frameworks to increase speed and ease of development
• Experience with temporal data and/or sequential modeling
• Experience with code quality and systems safety processes for production code delivery, with respect to data-driven methodologies and model validation
• Strong, practical understanding of real-time system development, performance issues, testing modalities, and tradeoffs
• Ability to write code in C++ and python
• Ability to lead in globally distributed team
• You are an excellent communicator, skilled collaborator, and principled colleague

NICE TO HAVES

• Published research at top-tier conferences (NeurIPs, CVPR and similar)
• Proven track record of deploying ML models at scale in self-driving or related fields.
• Experience with computer vision (e.g.multi-view geometry, camera calibration, depth estimation, neural radiance fields, gaussian splatting, simultaneous localization and mapping)
• Experience with robot motion planning (e.g., trajectory optimization, sampling-based planning, model predictive control)
• Japanese language skills

For positions based in Palo Alto, CA, the base pay for this position ranges from $189,000- $310,500 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.