AI Research Scientist: Uncertainty Definition and Estimation

22 hours ago


Mountain View, California, United States Gatik AI Full time
About the Role

We are seeking a highly skilled Research Scientist to join our team at Gatik AI, a leader in autonomous middle mile logistics. As a Research Scientist, you will play a key role in designing and refining machine learning algorithms that enable our trucks to safely navigate and operate in complex, dynamic environments.

Key Responsibilities
  • Define and estimate uncertainty at different levels of autonomous driving
  • Develop and implement methods for data-dependent uncertainty estimation and anomalous input detection
  • Design and evaluate machine learning model-based uncertainty estimation and anomalous output detection
  • Mine and generate out-of-distribution examples to enhance model robustness
  • Mitigate the negative effects of uncertainty propagation in autonomous systems
  • Collaborate with the AI Research team to advance internal education and external scientific image
  • Work closely with production teams to deploy research findings and push the boundaries of autonomous trucking
Requirements
  • Ph.D. in Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related field
  • At least 1-3 years of hands-on experience in autonomous driving, robotics, or deep learning
  • Strong foundation in data structures, algorithm design, and complexity analysis
  • Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning frameworks like TensorFlow/PyTorch
  • Demonstrated ability to publish research findings in top-tier technical journals and conferences
About Gatik AI

Gatik AI is a leader in autonomous middle mile logistics, delivering goods safely and efficiently using its fleet of light and medium-duty trucks. We are committed to creating a diverse and inclusive environment where everyone feels they have opportunities to succeed and grow. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.



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