Machine Learning Engineer - Perception, Odometry and Localization

Reposted 19 Days Ago
Palo Alto, CA
Hybrid
140K-230K Annually
Mid level
Automotive • Software • Automation
The Role
Develop advanced sensor fusion algorithms for autonomous driving, lead ML model R&D, and collaborate with teams to enhance vehicle localization capabilities.
Summary Generated by Built In
Woven by Toyota is 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
At Woven by Toyota, the vehicle perception odometry and localization team develops algorithms that power production-ready autonomous driving (AD) and advanced driver assistance (ADAS) systems. Our team is responsible for building algorithms that provide cornerstone information about vehicle state and location within a sparse low-fidelity map. We seek to leverage the state-of-the-art from probabilistic inference and machine learning to build novel sensor fusion methods that will expand the capabilities of Toyota vehicles.

WHO ARE WE LOOKING FOR?
We are looking for a skilled developer to help build state-of-the-art sensor fusion algorithms to provide odometry and localization information critical to an autonomous driving stack. A strong candidate will have expertise in ML model development and model deployment, along with proficiency in data handling and software engineering practices. Background in modern filtering and estimation techniques to extract desired state from vision, inertial, and GNSS sensors is a plus.

Our vehicle perception odometry and localization team has a collaborative culture. We’re looking for a strong team player with a passion to innovate and deliver a product to the customer.

We recognize the unique capabilities each team member brings and encourage applicants to reach out even if they do not match all of the characteristics described below.

RESPONSIBILITIES

  • Contribute to ML model R&D by prototyping, validating, and iterating on existing and new model architectures for vehicle state estimation.
  • Own end-to-end development of new ML models, from data strategy, initial development, optimization, production platform validation, and fine-tuning based on metrics and on-road performance.
  • Write high-quality code, provide thorough code and design document reviews, and deliver rigorous reports from data-driven experiments.
  • Work in a high-velocity environment and employ agile development practices.
  • Team player and “get things done” mentality.
  • Collaborate closely with stakeholders in downstream customer teams to define interfaces, requirements, and validation.

MINIMUM QUALIFICATIONS

  • MS or higher degree in CS/CE/EE, or equivalent industry experience.
  • Extensive experience with sensor fusion problems.
  • 3+ years of experience with ML frameworks such as PyTorch or Tensorflow
  • 3+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization.
  • Strong programming skills in C++ and Python.
  • Passionate about applying ML methodology to advance self-driving technology.
  • Strong communication skills and the ability to communicate concepts clearly and precisely.
  • Experience in production-level software development best practices.

NICE TO HAVE

  • Experience in developing vision-first perception and mapping ML models.
  • HandExperience in runtime optimization for mission-critical systems on Linux and UNIX-like real-time operating systems.
  • s-on experience with building algorithms for autonomous systems.
  • Experience with automotive-grade edge-compute platforms.
  • Experience with building safety-critical software architectures

For positions based in Palo Alto, CA, the base pay for this position ranges from $112,000- $184,000 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.

Top Skills

C++
Python
PyTorch
TensorFlow
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The Company
Palo Alto, , California
1,679 Employees
Year Founded: 2023

What We Do

Woven by Toyota will help to deliver the safest, most intelligent mobility experiences and lifestyle for Toyota customers everywhere. At Woven by Toyota, we envision a human-centered future, where world-class technology expands global access to mobility, enhances the capabilities of drivers, and empowers people to thrive. We achieve this with a unique global culture that weaves modern Silicon Valley innovation with Japanese quality craftsmanship. As society, technology and customer needs evolve, we continuously pursue new ways to create a more personal, seamless experience for customers.

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