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Deep Learning Developer Jobs in Texas (NOW HIRING)

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

About the team Avride develops autonomous vehicle and delivery robot technology, leveraging deep ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

About the team Avride develops autonomous vehicle and delivery robot technology, leveraging deep ... About the role We are hiring experienced Machine Learning Engineers across Senior, Staff, and ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Design, implement, and refine deep learning models to ensure efficiency, scalability, and ... Avride is a developer and operator of autonomous vehicles and delivery robots. Founded in 2017, the ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

SIMILAR CAREER TITLES Data Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Lawrence Harvey

Senior Machine Learning Engineer

Austin, TX · On-site

$210K - $260K/yr

* Senior Machine Learning Engineers needed for high growth tech company * Austin, TX - must be ... Familiarity with large-scale deep learning architectures used for recommendation or ranking systems ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

Design, implement, and refine deep learning models to ensure efficiency, scalability, and ... Avride is a developer and operator of autonomous vehicles and delivery robots. Founded in 2017, the ...

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All JobsDeep Learning Developer JobsDeep Learning Developer Jobs in Texas

Deep Learning Developer information

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 in Texas are hiring for Deep Learning Developer jobs? Cities in Texas with the most Deep Learning Developer job openings:
Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Algorithm Engineer, Deep Learning & Vision

Bot Auto

Houston, TX

$99K - $137K/yr

Full-time

Posted 12 days ago

Job description

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.

Key Responsibilities
  • Explore and propose new ideas using your knowledge and experience in deep learning, neural networks and large foundation models in autonomous driving including: end-to-end object detection, tracking and prediction, end-to-end planning and control, and end-to-end autonomous driving system, end-to-end online mapping. SLAM in localization and etc..
  • Work on the entire life cycle of machine learning projects from data analysis, model experimentations to performance metrics verifications, and understand the entire workflow in great detail.
  • Be exposed to many cross-team projects and collaborate with the product, simulation and other sibling autonomous driving algorithm teams to extend machine learning technology to all components.
QualificationsRequired: 
  • Have an advanced degree (Ph.D or Master's) in related fields of study: computer science, computer engineering, robotics, mathematics, physics, and etc.
  • Have in-depth knowledge and extensive experience in machine learning, and/or computer vision, modern transformer architecture, and employ SOTA techniques of machine learning.
  • Be familiar with PyTorch, TensorFlow and other machine learning platforms and tools.
  • Have strong motivation to work independently in a fast paced environment while collaborating with other teams on more complex and larger projects.
Preferred: 
  • Have a proven track record of research publications in top conferences and/or journals as the first author.
  • Have knowledge and experience of generative models, model distillation, or model inference acceleration (e.g. TensorRT) techniques.

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