Machine Learning Engineer, Perception

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 Machine Learning Engineer to join our Perception team . This role is hybrid based in Palo Alto, CA . You will be at the forefront of advancing our autonomous drone delivery system, leveraging deep learning to ensure our aircraft navigate the world with precision and safety.  At Wing, you aren’t just building models in a vacuum; you have access to tens of thousands of hours of flight data from a diverse sensor suite. Your improvements will deploy directly to a large fleet of autonomous aircraft, impacting thousands of real-world customers daily. We value senior engineers who are intrinsically driven and have a knack for solving complex problems with stunningly simple, pragmatic solutions. What You’ll Do:  Design & Deploy: Build and deploy highly reliable ML solutions both for the backend as well as optimized for resource-constrained, real-time environments. Monitor and Improve: Support and improve existing ML models and infrastructure, sharing in the team’s expertise. Collaborate: Partner across hardware, software, and flight-testing teams to take features from concept to production-ready flight code. What You’ll Need:  3+ years of experience in ML, deep learning, or computer vision, ideally within robotics or autonomous systems. MS degree in Computer Science, Robotics, Aerospace, Mechanical Engineering or 2 years of experience working on problems involving above mentioned skills in a directly related field Excellent software design and implementation skills Proficiency in Python and/or C++. Hands-on experience with JAX, PyTorch, or TensorFlow, building training/inference/validation pipelines. Familiarity with  modern CV architectures (CNNs, Transformers, etc.). Domain Expertise: Hands on experience in one or more of the following domains: Multi-view Geometry & 3D Reconstruction. Monocular or Stereo Depth Estimation. Object detection, localization, Semantic Segmentation. Local and global image features Vision foundation models, VLMs, VLAs Ability to design and implement well thought-out simple solutions to business critical problems The US base salary range for this full-time position is the salary range below + bonus + equity + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process. Salary Range $190,000 — $202,000 USD 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 .