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AI Research Scientist

1 month ago

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

We're seeking a highly skilled Research Scientist to join our team at Gatik AI, a leader in autonomous middle mile logistics. As a key member of our AI Research team, you will play a vital role in developing novel end-to-end algorithms for our Autonomy Stack, focusing on foundation models for driving, robust, interpretable, and explainable Autonomous Driving models, and pushing the boundaries of what's possible in autonomous trucking.

Key Responsibilities
  • Develop novel end-to-end algorithms for Autonomy Stack
  • Conduct research on foundation models for driving
  • Develop robust, interpretable, and explainable Autonomous Driving models
  • Push forward the cutting-edge AI large/foundation model-related methods for use in the Autonomy Stack for any subset of Mapping, Perception, Planning, and Selection
  • Test ML models in simulation to ensure robust performance and generalization
  • Analyze model performance and identify areas for improvement, iterating on design and implementation to enhance quality and reliability
  • Participate in the AI Research team activities targeting internal education and external scientific image
  • Work closely with the Production teams to push your idea into deployment
  • Propose new ideas and build on top of state-of-the-art knowledge
Requirements
  • Ph.D. in one or more of the following areas: Electrical Engineering, Computer Science, Robotics, Artificial Intelligence, Mathematics, or a related field
  • At least 1-3 years of hands-on experience in one or more of the following areas: Autonomous Driving (preferable), Robotics, or Deep Learning in general
  • At least 1-3 years of research experience in one or more of the following areas: Foundation Modeling (preferable), Perception/Behavior, Computer Vision, Statistics, Probability theory
  • Deep knowledge of Autonomous Driving, including differentiable E2E Autonomous Driving modeling, Visual Language Model (VLM)/Multimodal Large Language Model (MLLM)-based approach, foundation model interpretability: end2end vs modular approach, sensor simulation specifics, and Transformer-based Pipeline
  • Experience with sensor and behavior simulation environments for autonomous vehicles, such as CARLA, Waymax, or similar platforms
  • 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, including Deep Learning frameworks like TensorFlow/PyTorch
  • Demonstrated ability to publish research findings in top-tier technical journals and conferences (ICRA, CoRL, IROS, ICLR, ICML, NeurIPS, AAAI, IJCAI, CVPR, ICCV, ECCV, etc.)
  • Passion for Autonomous Driving