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Deep Learning Scientist Jobs in Texas (NOW HIRING)

Targeted Talent

Senior Deep Learning Engineer

Austin, TX · On-site +1

$130K - $180K/yr

Bachelor's degree in Computer Science, Engineering, or related field * 5+ years of experience, with at least 2 years in both deep learning and software engineering * Proficiency in deep learning ...

Nvidia

Senior Deep Learning Compiler Engineer

Austin, TX

$103K - $142K/yr

D. in Computer Science, Computer Engineering, related field or equivalent experience * 3+ years of ... MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as ...

Nvidia

Senior GPU Architect, Deep Learning

Austin, TX · On-site

MS in Computer Science, Electrical Engineering or Computer Engineering or equivalent experience. * Experience in working with hardware targeted at deep learning, or working on mapping deep learning ...

Avride

Machine Learning Engineer

Austin, TX · On-site

About the team Avride develops autonomous vehicle and delivery robot technology, leveraging deep ... Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. * Experience ...

Avride

Machine Learning Engineer

Austin, TX · On-site

About the team Avride develops autonomous vehicle and delivery robot technology, leveraging deep ... Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. * Experience ...

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All JobsDeep Learning Scientist JobsDeep Learning Scientist Jobs in Texas

Deep Learning Scientist information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do deep learning scientist jobs pay per year?

As of Jul 26, 2026, the average yearly pay for deep learning scientist in Texas is $114,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Deep Learning Scientist, and why are they important?

To thrive as a Deep Learning Scientist, you need a solid background in machine learning, statistics, and programming, often supported by an advanced degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and proficiency in Python are typically required. Strong problem-solving skills, creativity, and the ability to communicate complex ideas clearly set outstanding candidates apart. These capabilities are essential for developing innovative AI solutions, interpreting results, and collaborating effectively in multidisciplinary teams.

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

AspectDeep Learning ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; strong background in deep learning frameworksBachelor's or Master's in Computer Science or related fields; proficiency in machine learning algorithms and software engineering
Work EnvironmentResearch-focused, experimental, often in R&D teamsDevelopment and deployment-focused, working on production systems
Employer & Industry UsageTech companies, research labs, AI startupsTech firms, finance, healthcare, and industries deploying ML models

While both roles involve machine learning, Deep Learning Scientists focus on developing advanced neural network models and research, whereas Machine Learning Engineers implement, optimize, and deploy these models in real-world applications.

What are Deep Learning Scientists?

Deep Learning Scientists are experts who design, develop, and implement advanced machine learning models inspired by the structure and function of the brain, known as artificial neural networks. They work with large datasets to train algorithms that can recognize patterns, make predictions, and solve complex problems in areas such as image recognition, natural language processing, and autonomous systems. Deep Learning Scientists often collaborate with software engineers, data scientists, and domain specialists to deploy models in real-world applications like healthcare, finance, and self-driving cars.

Will MLE be replaced by AI?

As a Deep Learning Scientist, machine learning engineering (MLE) involves designing and deploying models, which AI advancements can automate or enhance. However, MLE roles require expertise in data handling, model optimization, and domain knowledge that AI tools support but do not fully replace. Human oversight remains essential for ensuring model accuracy, ethical considerations, and system integration.

What are some typical challenges faced when working as a Deep Learning Scientist, and how can they be addressed?

Deep Learning Scientists often encounter challenges such as managing large datasets, tuning complex model architectures, and ensuring reproducibility of experiments. Handling these issues requires strong skills in data preprocessing, familiarity with version control systems, and experience with frameworks like TensorFlow or PyTorch. Collaborating closely with cross-functional teams—including data engineers, software developers, and domain experts—can also help in overcoming technical and project-related obstacles. Continuous learning and staying updated with the latest research is essential to excel in this rapidly evolving field.

Which 3 jobs will survive AI?

Deep Learning Scientists are likely to continue to be in demand as AI advances, especially in research, model development, and complex problem-solving roles. Jobs that require high levels of creativity, emotional intelligence, or physical dexterity, such as healthcare professionals, skilled trades, and creative artists, are also expected to persist. Combining technical skills with domain expertise will enhance job security in an AI-driven future.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Scientist or AI executive, with compensation including salary, bonuses, and stock options. These roles often require advanced expertise in machine learning, deep learning frameworks, and extensive industry experience, and they are usually found in leading tech companies or AI-focused organizations.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like Deep Learning Scientist, are generally well-paid due to the specialized skills required, such as programming in Python, experience with neural networks, and knowledge of frameworks like TensorFlow or PyTorch. Salaries vary based on experience, location, and industry, but these roles tend to offer above-average compensation compared to many other tech jobs.
What are popular job titles related to Deep Learning Scientist jobs in Texas? For Deep Learning Scientist jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Deep Learning Scientist jobs in Texas look for? The top searched job categories for Deep Learning Scientist jobs in Texas are:
What cities in Texas are hiring for Deep Learning Scientist jobs? Cities in Texas with the most Deep Learning Scientist job openings:
Deep Learning Scientist jobs near you
Infographic showing various Deep Learning Scientist job openings in Texas as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.
Senior Deep Learning Engineer

Senior Deep Learning Engineer

Targeted Talent

Austin, TX • On-site, Remote

$130K - $180K/yr

Full-time

Posted 15 days ago

Job description

We're seeking top-notch engineers to join our team. As part of our group, you'll collaborate with hardware and software engineers to design, develop, and optimize software for our chip, making AI inference accessible to everyone. You'll excel in identifying and resolving functional/performance bottlenecks in complex software and hardware designs.

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model optimization pipeline. If you thrive on pushing the boundaries of AI technology, this role is for you!

Requirements:

  • Bachelor's degree in Computer Science, Engineering, or related field
  • 5+ years of experience, with at least 2 years in both deep learning and software engineering
  • Proficiency in deep learning frameworks like Tensorflow and/or PyTorch
  • Experience with CNNs, LSTMs/RNNs, Transformers
  • Strong math skills and Python proficiency
  • Experience with C/C++

Preferred Skills & Experience:

  • Master's or PhD in Computer Science, Engineering, or related field
  • Experience in embedded or low-level programming
  • Knowledge of CUDA/OpenGL
  • Experience deploying neural networks in production
  • Familiarity with model compression techniques like quantization, pruning, etc.
These are permanent full time remote positions.
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Your single source for HR professional services, we offer job seekers specialized employment services, spanning contract, permanent positions, and project solutions for highly specialized and managerial level talent needs. Our team of specialized recruiters and consultants abilities extend far beyond resume or career counseling. With hundreds of collaborators strategically located throughout the country, our organization possess the local market knowledge and industry relationships that make successful geography-specific reach possible.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Vancouver, BC, CA

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