Autonomous Vehicle AI Engineer - Computer Vision and Path Planning

$115,290 - $161,406/Yr

Blue Origin - Seattle, WA

Full-time - Mid Level

Seattle, WA

Transportation Equipment Manufacturing

About the position

The Autonomous Vehicle AI Engineer at Blue Origin will focus on developing AI-driven computer vision and path planning algorithms to enhance autonomous navigation systems for space vehicles. This role is crucial in advancing safe human spaceflight and requires a commitment to quality and collaboration within a multidisciplinary team. The engineer will work in a fast-paced environment, contributing to innovative solutions that enable vehicles to interpret their surroundings and navigate complex environments autonomously.

Responsibilities

• Spearhead the development of AI-driven computer vision algorithms to accurately perceive and understand the vehicle's environment through sensor data.
• Design and implement sophisticated machine learning models for object detection, classification, semantic segmentation, and anomaly detection specific to autonomous driving scenarios.
• Innovate and develop state-of-the-art path planning algorithms that use predictive modeling and decision-making techniques to facilitate safe and efficient navigation of autonomous vehicles in dynamic conditions.
• Train, validate, and deploy neural networks capable of real-time performance in onboard vehicle systems, optimizing for accuracy, speed, and low-power consumption.
• Work collaboratively with a multidisciplinary team of engineers, researchers, and scientists to integrate AI/ML solutions into a comprehensive autonomous driving platform.
• Simulate and test autonomous driving algorithms using both synthesized data and real-world driving scenarios to ensure robustness.
• Provide thought leadership in AI/ML by keeping abreast of the latest research and trends in the field, with a focus on applications in autonomous vehicles.
• Optimize AI models for edge and cloud deployment, addressing challenges such as latency, model compression, and distributed computing for vehicle fleets.
• Develop metrics and validation strategies to quantitatively assess the performance of computer vision and path planning systems in varied conditions.
• Contribute to the continuous improvement of in-house machine learning pipelines and tools for data annotation, model training, and performance monitoring.
• Mentor junior AI engineers and actively participate in the AI/ML community.

Requirements

• Master's or PhD in Computer Science, Robotics, AI, Machine Learning, or a closely related field, with a strong emphasis on autonomous systems.
• Proven experience in applying deep learning in computer vision, preferably in the context of autonomous vehicles or robotics.
• In-depth understanding of sensor fusion, environmental perception, and spatial-temporal reasoning for autonomous navigation.
• Strong proficiency in Python, C++, and deep learning libraries (TensorFlow, PyTorch) along with experience using simulation and visualization tools.
• Demonstrable experience in path planning algorithms, including probabilistic planning, graph-based methods, and optimal control for vehicle trajectory generation.
• Ability to work hands-on with hardware and software debugging in a real-world automotive testing environment.
• Ability to work in a fast-paced, cross-functional team atmosphere and deliver results under tight deadlines.
• Ability to earn trust, maintain positive and professional relationships, and contribute to a culture of inclusion.
• Exceptional analytical skills and the capability to tackle problems with creative solutions.
• Excellent communication skills to effectively share complex technical information with other team members and stakeholders.

Benefits

• Medical, dental, vision, basic and supplemental life insurance
• Paid parental leave
• Short and long-term disability
• 401(k) with a company match of up to 5%
• Education Support Program
• Paid Time Off: Up to four (4) weeks per year based on weekly scheduled hours, and up to 14 company-paid holidays
• Discretionary bonus designed to reward individual contributions and allow employees to share in company results.