Autonomous Vehicle AI Engineer III (Computer Vision)

TL;DR

Autonomous Vehicle AI Engineer III (Computer Vision and Path Planning): Developing AI-driven perception and navigation systems for space vehicles with an accent on computer vision, sensor fusion, and path planning. Focus on deploying real-time neural networks on flight-qualified hardware and building high-fidelity simulation environments to validate autonomous maneuvers.

Location: Greater Seattle Area. Applicants must be a U.S. citizen, national, permanent resident (Green Card holder), or lawfully admitted as a refugee/granted asylum.

Salary: $164,652 - $230,512

Company

hirify.global is developing reusable, safe, and low-cost space vehicles to enable millions of people to live and work in space for the benefit of Earth.

What you will do

• Develop AI-driven computer vision algorithms for environment perception using cameras, LiDAR, and other sensors.
• Train and test ML models for object detection, classification, semantic segmentation, and anomaly detection.
• Implement path planning algorithms to ensure safe and efficient navigation during in-space operations.
• Optimize and deploy neural networks for real-time performance on flight-qualified hardware.
• Collaborate with multidisciplinary teams of GNC, software, and hardware engineers for system integration.
• Build high-fidelity simulation environments to validate autonomous algorithms against mission scenarios.

Requirements

• PhD in Computer Science, Robotics, AI, ML, Aerospace Engineering, or a Master's degree with relevant professional experience.
• Demonstrated experience applying deep learning to computer vision or decision-making.
• Strong theoretical understanding of sensor fusion, environmental perception, and path planning.
• High proficiency in Python and/or C++, and deep learning libraries such as PyTorch or TensorFlow.
• Must meet US Export Control Regulations (US citizenship or permanent residency).

Nice to have

• Experience training reinforcement learning (RL) agents for complex optimization or control problems.
• Experience with simulation environments like Gazebo or NVIDIA Isaac Sim.
• Familiarity with classical Guidance, Navigation, and Control (GNC) concepts.
• Experience with transformers and large machine learning models.
• Hands-on experience deploying and debugging software on embedded systems or robotic hardware.

Culture & Benefits

• Comprehensive medical, dental, and vision insurance.
• 401(k) with company match up to 5%.
• Up to four weeks of paid time off and 14 company-paid holidays.
• Paid parental leave, short-term and long-term disability.
• Education Support Program.