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Deep Learning Ai Jobs in Texas (NOW HIRING)

Bot Auto

Intern, Deep Learning Engineer

Houston, TX

$14.25 - $19/hr

We are looking for MS/PhD interns to join our core AI team for a 3-6 month internship to tackle ... Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ...

Bot Auto

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

We are looking for MS/PhD interns to join our core AI team for a 3-6 month internship to tackle ... Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ...

Targeted Talent

Senior Deep Learning Engineer

Austin, TX · On-site +1

$130K - $180K/yr

If you thrive on pushing the boundaries of AI technology, this role is for you! Requirements ... Proficiency in deep learning frameworks like Tensorflow and/or PyTorch * Experience with CNNs ...

NVIDIA

Senior Deep Learning Communication Architect

Austin, TX · On-site

$128K - $174K/yr

NVIDIA is a leader in computer graphics and AI technology, seeking a Senior Deep Learning Communication Architect to enhance the performance of deep learning systems. The role involves optimizing ...

Nvidia

Senior Deep Learning Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era ... NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and ...

Nvidia

Senior GPU Architect, Deep Learning

Austin, TX · On-site

We are now looking for a Senior GPU & Deep Learning Architect! The NVIDIA GPU Architecture group is ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

Nvidia

Senior Deep Learning Compiler Engineer - XLA

Austin, TX · On-site

$103K - $142K/yr

More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the ...

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Deep Learning Ai information

What is a deep learning AI professional?

Deep Learning AI professionals are experts who design, develop, and implement artificial intelligence systems that use deep neural networks to analyze complex data and solve tasks such as image recognition, natural language processing, and autonomous decision-making. They work with large datasets and advanced algorithms to build models that can learn and improve over time. These professionals often have a background in computer science, mathematics, or engineering, and are skilled in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive as a deep learning AI engineer?

To thrive as a Deep Learning AI Engineer, you need a strong background in mathematics, programming (especially Python), and experience with neural networks, typically supported by a degree in computer science, engineering, or a related field. Proficiency with deep learning frameworks such as TensorFlow or PyTorch, and knowledge of tools like CUDA for GPU acceleration, are essential; relevant certifications can be advantageous. Analytical thinking, creativity, and effective communication are important soft skills for solving complex problems and collaborating with cross-functional teams. These skills and qualities are crucial for building robust AI models and driving innovation in this rapidly evolving field.

What are some common challenges faced by professionals working in deep learning AI, and how can they be addressed?

Professionals in Deep Learning AI often encounter challenges such as managing large datasets, ensuring model accuracy, and addressing issues like overfitting. Collaboration with data engineers and domain experts is crucial to ensure high-quality data and relevant feature selection. Additionally, staying up-to-date with rapidly evolving frameworks and algorithms requires continuous learning and participation in knowledge-sharing within the team. Regular code reviews and experimentation with different architectures can help overcome technical obstacles and improve model performance.

What is the difference between Deep Learning Ai vs Machine Learning Engineer?

AspectDeep Learning AiMachine Learning Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of neural networksDegree in Computer Science, Data Science, or related fields; programming skills in Python, R
Work EnvironmentResearch labs, AI development teams, tech companies focusing on AI modelsSoftware development teams, data analysis projects across various industries
Industry UsagePrimarily in AI research, autonomous systems, NLP, computer visionAcross industries for predictive modeling, data analysis, automation

Deep Learning Ai specialists focus on designing and implementing neural network models for complex AI tasks, often requiring advanced knowledge of deep neural networks. Machine Learning Engineers develop broader machine learning models, including traditional algorithms. While both roles require similar educational backgrounds, Deep Learning Ai roles are more specialized in neural networks and AI research, whereas Machine Learning Engineers work across a wider range of algorithms and applications.

What are popular job titles related to Deep Learning Ai jobs in Texas?

For Deep Learning Ai jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Deep Learning Ai jobs in Texas look for?

The top searched job categories for Deep Learning Ai jobs in Texas are:

What cities in Texas are hiring for Deep Learning Ai jobs?

Cities in Texas with the most Deep Learning Ai job openings:

Deep Learning Ai jobs near you
Infographic showing various Deep Learning Ai job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Intern, Deep Learning Engineer

Bot Auto

Houston, TX

$14.25 - $19/hr

Full-time, Internship

Re-posted 18 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.

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