Intern, Deep Learning Engineer

Botauto; Houston (TX); On-site; USD 20,000 - 35,000; Full time

Job summary

Botauto in Houston is seeking MS/PhD interns to join their AI team for a 3-6 month internship. The role involves implementing and benchmarking next-gen architectures and owning a research project.

Ideal candidates are Master's or Ph.D. candidates in CS, Robotics, or similar fields, proficient in Python and PyTorch, and available full-time for at least 3 months.

Qualifications

• Current Master’s or Ph.D. candidate in CS, Robotics, or related fields focused on Deep Learning.
• Proficiency in Python and PyTorch with clean coding practices required.
• Solid understanding of modern AI architectures, especially Transformers.

Responsibilities

• Implement and benchmark next-gen architectures for autonomous trucking.
• Own a targeted research project under senior mentorship.
• Train, tune, and optimize deep learning models using large-scale compute clusters.

Skills

Python

PyTorch

Deep Learning

Computer Vision

Education

Current Master’s or Ph.D. candidate in CS, Robotics, or related fields

Tools

Linux

Git

C++

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.