Staff Machine Learning Engineer, Simulation

About the Role:

Wing is looking for a Staff Machine Learning Engineer, Simulation to join our Simulation team. This role is hybrid based in Palo Alto.

Simulation is a core technology for Wing. We provide essential tools for R&D and are critical to ensuring the reliability of our fleet of autonomous aircraft. The simulation team’s work spans vehicle physics and sensor modeling, large-scale simulation frameworks, test infrastructure for backend verification and integrated avionics and system testing.

The Staff Machine Learning Engineer, Simulation is a foundational role for someone who thrives on both technical execution and strategic growth. You will be a key driver in integrating advanced ML techniques into Wing’s simulation stack. You will define and execute the strategy for enhancing simulator realism, and develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms to model the real world.

What You’ll Do:

• Lead the design, development and deployment of world models and generative systems for realistic and controllable sensor generation for large-scale simulation at Wing’s autonomous system.
• Develop generative pipelines to build high-fidelity synthetic datasets, leveraging SOTA multimodal models, diffusion techniques and world-models to simulate complex 4D environments.
• Partner with research teams across Alphabet to integrate advanced modeling techniques.
• Champion sim-to-real efforts, using domain adaptation and transfer learning techniques to ensure our simulated models faithfully capture the behaviors of physical, on-vehicle systems.
• Apply VLMs to enhance the understanding and controllability of our world simulation products.
• Play a pivotal role in shaping the broader AI infrastructure across the organization, establishing best practices, optimizing workflow management for large-scale training, and championing foundational AI initiatives.

What You’ll Need:

• 12+ years of experience developing and designing machine learning applications, autonomous systems, or simulation platforms.B.S, M.S., or Ph.D. degree or equivalent practical experience in Computer Science, Machine Learning, Robotics, or a related field.
• Demonstrated ability to lead technical ML projects of significant scope and complexity, driving initiatives from research to production-ready solutions.
• Deep expertise in 3D World Modeling or 3D computer vision.
• Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting).
• In-depth knowledge of generative AI, predictive world models, autoregressive models, or self-supervised learning from multi-modal sensor streams.
• Hands-on experience with sim-to-real transfer, domain adaptation, and world models.
• Experience developing testing frameworks and evaluating ML models for edge cases and rare events in complex systems.