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Autonomous Vehicle AI Systems Engineer
2 months ago
We are seeking a highly skilled Principal Engineer to join our team at Blue Origin, where you will play a key role in developing cutting-edge autonomous vehicle AI systems. As a member of our Space Systems Development (SSD) business unit, you will be part of a multidisciplinary team that is shaping the future of space exploration.
Key Responsibilities- Develop AI-driven algorithms to enable vehicles to perceive, understand, and interact with their environment.
- Design and implement sophisticated machine learning models for object detection, classification, semantic segmentation, and anomaly detection in autonomous driving scenarios.
- Train, validate, and deploy neural networks capable of real-time performance in onboard vehicle systems, optimizing for accuracy, speed, and low-power consumption.
- Collaborate with cross-functional teams to integrate AI/ML solutions into a comprehensive autonomous driving platform.
- Simulate and test autonomous driving algorithms using synthesized data and real-world driving scenarios to ensure robustness.
- Provide thought leadership in AI/ML by staying up-to-date with 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 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.
- Master's or PhD in Computer Science, Robotics, AI, Machine Learning, or a closely related field, with a strong emphasis on autonomous systems.
- 10+ years of 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 deploying sense and act algorithms to enable safe and efficient control for vehicles.
- 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.
- 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.