Senior Machine Learning Engineer, Perception

2 days ago

Palo Alto, California, United States Wing Full time

About the Role

Wing is looking for a Senior Machine Learning Engineer to join as a foundational member of our ML Perception team. 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:
    Research, build and deploy highly reliable ML models optimized for resource-constrained, real-time environments.
  • Scale Research:
    Utilize Wing's massive datasets to develop and refine complex models that push the boundaries of environmental understanding.
  • Innovate:
    Apply state-of-the-art CV foundation models to solve real-world robotics challenges.
  • Collaborate:
    Partner across hardware, software, and flight-testing teams to take features from concept to production-ready flight code.
  • Mentor:
    Educate and drive ML/AI adoption at Wing.

What You'll Need:

  • 8+ years of experience in ML, deep learning, or computer vision, ideally within robotics or autonomous systems.
  • MS or PhD in Computer Science, Robotics, Electrical Engineering, or equivalent industry experience leading production-grade ML systems.
  • Proficiency in Python and/or C++.
  • Hands-on experience with JAX, PyTorch, or TensorFlow.
  • Deep understanding of Linear Algebra and modern CV architectures (CNNs, Transformers, etc.).
  • Domain Expertise: Proven track record in one or more of the following:
  • Multi-view Geometry & 3D Reconstruction.
  • Monocular or Stereo Depth Estimation.
  • Object detection, localization, Semantic Segmentation.
  • Local and global image features
  • The ability to drive complex features independently and a history of delivering simple, well-thought-out solutions to business-critical problems.
  • Publications at top-tier Robotics/CV/ML conferences such as CVPR, ICCV, ECCV, ICML, ICRA, RSS, NeurIPS.

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