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Deep Learning Developer Jobs in Houston, TX (NOW HIRING)

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

Intern, Deep Learning Engineer

Houston, TX · On-site

$14.25 - $19/hr

Train, tune, and optimize deep learning models using our large-scale compute clusters and truck ... Engineering Plus: Experience with Linux, Git, C++, or deployment tools like TensorRT/ONNX.

We're looking for a Machine Learning Engineer to drive our machine learning strategy. We are ... Experience with deep learning frameworks (Pytorch, JAX, TensorFlow, etc.) * Experience with cloud ...

New

Senior AI/ML Engineer

Texas City, TX · On-site

$89K - $122K/yr

Senior AI/ML Engineer Location: Texas Experience: 10+ Years Employment Type: Contract We are ... The ideal candidate should have strong expertise in Python, Machine Learning, Deep Learning ...

New

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Expertise in AI/ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and the end-to ... Strong programming skills in Python and proficiency with relevant libraries (e.g., NumPy, Pandas ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

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Deep Learning Developer information

See Houston, TX salary details

$17

$36

$48

How much do deep learning developer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for deep learning developer in Houston, TX is $36.71, according to ZipRecruiter salary data. Most workers in this role earn between $31.20 and $40.87 per hour, depending on experience, location, and employer.

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

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What is a deep learning developer?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

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

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges deep learning developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
What cities near Houston, TX are hiring for Deep Learning Developer jobs? Cities near Houston, TX with the most Deep Learning Developer job openings:
Infographic showing various Deep Learning Developer job openings in Houston, TX as of June 2026, with employment types broken down into 1% As Needed, 56% Full Time, 41% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $76,356 per year, or $36.7 per hour.

Intern, Deep Learning Engineer

Bot Auto

Houston, TX • On-site

$14.25 - $19/hr

Full-time, Internship

Re-posted 7 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.