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Intern, Deep Learning Engineer

Bot AutoHouston🇺🇸United States

Why this role stands out

Gain invaluable experience by prototyping state-of-the-art deep learning models and owning a research project within the exciting field of autonomous trucking. This hybrid internship is ideal for driven Master's or PhD candidates with strong Python and PyTorch skills looking to make a real-world impact and grow their expertise. Apply now to join a team at the forefront of innovation!

Quick overview

SeniorityEntry Level
Work modeHybrid
LocationHouston, United States
RoboticsComputer VisionDeep LearningAutonomous DrivingC++Generative AIGitPyTorchPythonData Analysis

Job description

About Bot Auto

Bot Auto is revolutionizing autonomous trucking by combining start-up agility with the wisdom of seasoned experts. We are looking for MS/PhD interns to join our core AI team for a 3-6 month internship to tackle real-world edge cases.

Key Responsibilities

  • SOTA Prototyping: Implement and benchmark next-gen architectures (e.g., Multi-modal perception, Online Mapping, Behavior Prediction, World Model).
  • Project Ownership: Own a targeted research project from data analysis to model verification under senior mentorship.
  • Scale Experimentation: Train, tune, and optimize deep learning models using our large-scale compute clusters and truck datasets.

Qualifications

Required:

  • Education: Current Master’s or Ph.D. candidate in CS, Robotics, or a related field, specifically focusing on Deep Learning, Computer Vision, Robotics, or related fields.
  • Technical Stack: Proficient in Python and PyTorch with clean coding practices.
  • Theoretical Core: Solid understanding of modern AI architectures, especially Transformers and its applications in different fields.
  • Commitment: Available full-time for at least 3 months.

Preferred:

  • Research Focus: Academic thesis or project experience in Multi-sensor Perception, Generative AI/Diffusion, Motion Prediction, or End-to-End Autonomous Driving.
  • Track Record: Publications or submissions at top conferences (e.g., CVPR, ICCV, NeurIPS, ICLR, ICRA).
  • Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

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