Hybrid Senior Machine Learning Engineer – World Foundation Model

at Woven Planet

• Job title: Senior Machine Learning Engineer – World Foundation Model
• Job type: Full Time
• Experience level: Senior
• Salary: $140,000 - $230,000 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Python, PyTorch, Tensorflow
• Location requirements: Hybrid, Palo Alto, United States

About the role

• Senior Machine Learning Engineer building vision-based world models for interactive driving scenarios. Applying advanced machine learning techniques for autonomous driving at Woven by Toyota.

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.

Requirements

• 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.

Benefits

• Excellent health, wellness, dental and vision coverage
• A rewarding 401k program
• Flexible vacation policy
• Family planning and care benefits