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Senior Machine Learning Engineer - World Foundation Model

Woven by Toyota
Posted 6 months ago, valid for 22 days
Location

Palo Alto, Santa Clara 94301, CA

Salary

$140,000 - $230,000 per year

Contract type

Full Time

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Sonic Summary

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  • Woven by Toyota is seeking a senior machine learning engineer with a minimum of 5 years of professional experience in computer vision, machine learning, or applied science.
  • The role involves developing a vision-based world model for interactive driving scenarios and requires strong communication skills for collaboration with internal teams and the Toyota Research Institute.
  • Candidates should have expertise in foundation models and large behavior models for robotics, with proficiency in PyTorch, JAX, or TensorFlow, along with strong Python and C++ skills.
  • The position offers a competitive salary ranging from $140,000 to $230,000 per year, depending on skills and experience, along with a comprehensive benefits package.
  • Woven by Toyota is committed to fostering a diverse and inclusive work environment while providing support for employees and their families.

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, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep learning and optimization, particularly in complex visual scenarios. We're seeking passionate innovators and creative problem-solvers eager to redefine mobility through cutting-edge AI and robotics, contributing directly to shaping the future of self-driving technology.

 

Woven by Toyota is developing a joint project between Toyota Research Institute (TRI) and Woven by Toyota to research and develop a visual-based world model as a learned simulator to evaluate end-to-end automated driving. This cross-org collaborative project is synergistic with TRI's automated driving advanced development division's efforts in Diffusion Policy and Large Behavior Models (LBM).

 

WHO ARE WE LOOKING FOR?

A senior machine learning engineer to help build a vision-based world model for interactive driving scenarios. The engineer will also help bridge the connections between the research project and the production programs. This role requires strong communication skills and a collaborative mindset to navigate the joint nature of the Woven / TRI collaboration. The applicant is expected to have a wide technical knowledge of the state-of-the-art approaches in robotics/automated driving to define vision, scope, and to initiate longer-term open-research efforts.

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RESPONSIBILITIES
  • Support the development and benchmarking of state-of-the-art world foundation models for autonomous driving, ranging from data strategy, multistage training, model selection, and eventual deployment and integration with onboard and offboard applications. 
  • Build visually realistic simulators to evaluate full end-to-end autonomy stack behavior, from simulating sensors to policy rollouts, across a diverse range of scenario conditions.
  • Research and implement cutting-edge approaches across domains (reinforcement learning, probabilistic & generative modeling, scene representations, sensor fusion, temporal reasoning) and validate their effectiveness in simulation and through real-world driving performance.
  • Collaborate with various company-internal teams as well as TRI, providing technical mentorship and fostering a collaborative, high-trust engineering culture across organizational boundaries, influencing technical decisions across the partnership, and possibly co-authoring publications for premier conferences and journals.
  • Increase the scalability of ML pipelines to support the training and inference of large foundation models, and to optimize edge deployment of state-of-the-art architectures.
  • Curate scenarios, develop system introspection capabilities, and establish frameworks for understanding model behavior and performance at scale.


MINIMUM QUALIFICATIONS
  • MS or PhD in computer vision, ML, robotics, or related quantitative fields.
  • 5+ years of professional experience with computer vision, ML, or applied science.
  • Strong hands-on experience with foundation models, world models, generative AI, multimodal transformers, diffusion, VLAs, or large end-to-end behavior models for robotics or autonomy.
  • Expertise in PyTorch (preferred), JAX, or TensorFlow; strong Python and C++ skills.
  • Strong understanding of temporal/sequential modeling, probabilistic modeling, reinforcement learning, Bayesian inference, state-space models, and uncertainty quantification.
  • Strong understanding of 3D perception, multi-view geometry and sensor fusion.
  • Hands-on experience with large-scale distributed training, ML workflows (data curation, training, evaluation, deployment), and inference optimization.
  • Knowledge of debugging, profiling and deploying deep neural networks with NVIDIA tooling (CUDA, Nsight, TensorRT) and ONNX.
  • Experience with simulation platforms (e.g., CARLA, Applied Intuition, Nvidia DriveSim, etc.), their internal principles and their integration into autonomous system workflows.


NICE TO HAVES
  • Publications at top-tier venues (e.g. NeurIPS, CVPR, ICML, ICRA, RSS).
  • Experience with closed-loop simulation validation, scenario generation, rare-event or counterfactual testing.
  • Experience with multi-agent simulation or high-fidelity 3D environments and game engines (e.g Unreal).
  • Experience with 3D generation or reconstruction (e.g., Gaussian Splatting, NeRFs).
  • Prior experience in fast-paced R&D environments bridging research and production.


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For positions based in Palo Alto, CA, the base pay ranges from $140,000 - $230,000 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.




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By applying, a Sonicjobs account will be created for you. Sonicjobs's Privacy Policy and Terms & Conditions will apply.

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