Intern, Deep Learning Engineer
Bot Auto · On-site
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Job details
- Work model
- On-site
- Salary
- Not listed by source
- Location
- Houston, TX
What the role asks for
What you'd do
- 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.
What they're asking for
- 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.Education
- Technical Stack: Proficient in Python and PyTorch with clean coding practices.Skill
- Theoretical Core: Solid understanding of modern AI architectures, especially Transformers and its applications in different fields.Skill
- Commitment: Available full-time for at least 3 months.Skill
- Research Focus: Academic thesis or project experience in Multi-sensor Perception, Generative AI/Diffusion, Motion Prediction, or End-to-End Autonomous Driving.SkillPreferred
- Track Record: Publications or submissions at top conferences (e.g., CVPR, ICCV, NeurIPS, ICLR, ICRA).SkillPreferred
- Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.SkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
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.