Staff Machine Learning Engineer, Simulation

Wing; San Francisco (CA); Hybrid; USD 274,000 - 292,000; Full time

Job summary

Wing is seeking a Staff Machine Learning Engineer, Simulation to join our Simulation team in a hybrid role based in Palo Alto. This role focuses on integrating advanced ML into Wing’s simulation stack used for autonomous aircraft.

You will lead world modeling efforts, build synthetic data pipelines, and collaborate with Alphabet researchers to improve simulator realism and scale AI infrastructure across the organization.

Qualifications

• Requires advanced degree or equivalent practical experience in CS/ML/Robotics.
• Proven ability to lead large ML projects from research to production.
• Deep expertise in 3D world modeling or 3D computer vision.
• Experience with sim-to-real transfer and domain adaptation.
• Experience with testing ML models for edge cases in complex systems.

Responsibilities

• Lead design, development and deployment of world models and generative systems for realistic sensor generation in large-scale simulation.
• Develop generative pipelines to build high-fidelity synthetic datasets using multimodal models and diffusion techniques.
• Collaborate with Alphabet researchers to integrate modeling techniques.
• Advance sim-to-real efforts with domain adaptation and transfer learning.
• Apply vision-language models to enhance world simulation products.
• Shape AI infrastructure, optimize large-scale training workflows, and champion foundational AI initiatives.

Skills

12+ years experience ML/simulation

Lead ML projects

3D world modeling

3D computer vision

Generative AI

Sim-to-real transfer

Testing ML in complex systems

Education

Ph.D. or equivalent in CS/ML/Robotics

Tools

3D Gaussian Splatting

Job description

About Wing

Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google’s parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you’re ready to do the greatest work of your life, come join us.

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.

Salary Range: $274,000 USD - $292,000 USD

Equal Opportunity Statement

Wing is an equal opportunity employer and it is Wing’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person’s merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.

If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our Candidate Accommodations Request Form.