Staff Software Engineer, Operations Research

Wing•Palo Alto, CA

6d•$274,000 - $292,000•Hybrid

About The Position

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. Wing is looking for a Staff Software Engineer, Operations Research to join our Delivery Network team. This role is hybrid based in Palo Alto, CA. As a Staff Software Engineer, Operations Research, you will own the mathematical foundation of our delivery network. Moving physical goods through the sky autonomously introduces dynamic constraints: battery conditions, real-time weather patterns, airspace de-confliction, and shifting marketplace demand. You will dive into a wealth of flight and logistics data, using advanced optimization techniques to maximize value for our consumers, our partners, and our fleet. You will exercise independent judgment to define our technical roadmap and bridge the gap between abstract mathematical models and our production environment. You will leverage advanced solvers and simulations to build solutions that scale with Wing's business.

Requirements

12+ years of industry or post-graduate experience solving complex optimization problems using mathematical programming or metaheuristics.
Ph.D. or Master's degree in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a closely related field.
Strong coding ability in Python, C++, or Java. You must understand object-oriented programming, functional programming concepts, and core computer science algorithms.
A proven track record of designing algorithms that don't just live in research papers, but operate efficiently in real-time production software systems.
Previous experience in aviation, autonomous vehicles, ride-sharing, or last-mile logistics.
Deep familiarity with other commercial or open-source optimization solvers (e.g., Gurobi, CPLEX, SCIP).
Experience with cloud computing platforms (GCP, AWS) and integrating solvers into scalable, distributed systems.
Experience modeling systems for simulation and designing experiments. We use a combination of discrete event simulations and high fidelity physics simulations.

Responsibilities

Design and Implement Algorithms: Build new algorithm components within our production delivery network system to meet emerging requirements. We work with Google OR-Tools and the researchers that develop it.
Extract Data-Driven Insights: Analyze complex logistics data to identify network inefficiencies, translating those insights directly into production-ready algorithm enhancements.
Integrate OR and ML: Combine state-of-the-art optimization and machine learning techniques (e.g., using ML for demand forecasting and Tools for fleet positioning) to improve the speed and quality of our dispatching decisions.
Lead Cross-Functionally: Collaborate tightly with software engineers, data scientists, hardware teams, and product managers to develop scalable, cross-cutting solutions that balance physical constraints with business value.
Exercise Strategic Autonomy: Evaluate technical options, make informed architectural decisions, and determine the appropriate OR methodologies to solve ambiguous, open-ended problems.
Mentorship: Elevate the technical rigor of the team by guiding junior scientists and engineers in OR fundamentals, code quality, and algorithm design.