Intern, Deep Learning Engineer at Bot Auto

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.

About Bot Auto

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.