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Deep Learning Research Intern Jobs in Texas (NOW HIRING)

Bot Auto

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

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 ...

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How much do deep learning research intern jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for deep learning research intern in Texas is $15.75, according to ZipRecruiter salary data. Most workers in this role earn between $13.22 and $17.64 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning research intern?

To thrive as a Deep Learning Research Intern, you need a strong grasp of machine learning fundamentals, programming skills (especially in Python), and a background in mathematics or computer science, often supported by relevant coursework or research experience. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and proficiency in using data processing and visualization tools are typically expected. Creativity, problem-solving abilities, and effective communication help interns contribute novel ideas and collaborate within research teams. These skills are vital for developing, testing, and presenting cutting-edge AI models and solutions in a fast-evolving field.

What does a deep learning research intern do?

A Deep Learning Research Intern assists in the development and experimentation of machine learning models, particularly neural networks, to solve complex problems in fields like computer vision, natural language processing, or robotics. They typically work under the guidance of experienced researchers, contributing to tasks such as data preprocessing, model training, and result analysis. Interns may also help implement and optimize algorithms, read and summarize research papers, and prepare reports or presentations on their findings. This role provides hands-on experience with state-of-the-art AI technologies and research methodologies.

What are some common challenges faced by deep learning research interns, and how can they overcome them?

Deep Learning Research Interns often encounter challenges such as managing complex datasets, tuning neural network architectures, and keeping up with the latest research developments. It's common to spend significant time troubleshooting code or optimizing models for better performance. Collaborating closely with mentors and team members, actively participating in research discussions, and consistently reading recent papers can help interns overcome these hurdles. Utilizing open-source tools and frameworks, along with clear documentation practices, also streamlines the research process.

What are the most commonly searched types of Deep Learning Research jobs in Texas?

The most popular types of Deep Learning Research jobs in Texas are:

What cities in Texas are hiring for Deep Learning Research Intern jobs?

Cities in Texas with the most Deep Learning Research Intern job openings:

Deep Learning Research Intern jobs near you

Intern, Deep Learning Engineer

Bot Auto

Houston, TX • On-site

$14.25 - $19/hr

Full-time, Internship

Re-posted 14 days ago

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.

Apply