Senior AI Engineer – Autonomy & Vision for UAVs

Honeywell Aerospace; Phoenix (AZ); On-site; USD 160,000 - 230,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) match

Paid holidays

Job summary

Honeywell Aerospace seeks a Lead AI Engineer to provide technical leadership in AI, computer vision, and autonomy for aerial vehicle platforms. You will craft multi-year research plans and drive development of AI technologies for autonomous operations, including navigation and obstacle detection.

The role includes pursuing government and internal funding, guiding a global team of scientists and engineers, and delivering scalable AI solutions for UAV/UAM platforms.

Qualifications

• Master's or PhD in a technical discipline (robotics, aerospace engineering, or related).
• Minimum 5 years' experience developing AI or computer vision for autonomy and aerospace applications.
• Track record of proposing and winning government contracts (>$500k).
• Expertise in R&D of computer vision and AI for aerospace.
• Experience leading complex R&D programs for internal and external customers.
• Ability to lead direct and indirect reports by influence.

Responsibilities

• Lead the development of complex AI solutions addressing business needs with scalability and robustness.
• Drive AI, computer vision, and autonomy strategy.
• Lead research into new techniques for AI in aerospace applications.
• Oversee transitions and productization of AI/vision tech for UAV/UAM platforms.
• Mentor AI engineers and foster a culture of innovation.

Skills

AI & CV for aerospace autonomy

Leadership & influence

Proposal writing

Python

TensorFlow

PyTorch

Education

Master's or PhD in robotics/aerospace/related field

Tools

Python

TensorFlow

PyTorch

DARPA/ARL grant experience

Job description

Honeywell Aerospace seeks a Lead AI Engineer to provide technical leadership in AI, computer vision, and autonomy for aerial vehicle platforms. You will craft multi-year research plans and drive development of AI technologies for autonomous operations, including navigation and obstacle detection.

The role includes pursuing government and internal funding, guiding a global team of scientists and engineers, and delivering scalable AI solutions for UAV/UAM platforms.