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Deep Learning Engineer Jobs in Austin, TX (NOW HIRING)

Nvidia

Senior Deep Learning Performance Architect

Austin, TX · On-site

$165K/yr

Strong programming skills in Python and C++. Ways to stand out from the crowd: Solid fundamental ... GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

CesiumAstro is a developer and pioneer of communication systems for satellites and airborne ... Responsibilities : • Design, develop, and maintain deep learning pipelines for real-time data ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

CesiumAstro is a developer and pioneer of innovative communication systems for satellites and ... Responsibilities : • Design, develop, and maintain deep learning pipelines for real-time data ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

Demonstrated experience in deep learning and transformers models * Proficiency in frameworks like PyTorch or Tensorflow * Strong foundation in data structures, algorithms, and software engineering ...

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Showing results 21-40

All JobsDeep Learning Engineer JobsDeep Learning Engineer Jobs in Austin, TX

Deep Learning Engineer information

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$37.7K

$114.8K

$189.8K

How much do deep learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for deep learning engineer in Austin, TX is $114,846.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,300.00 and $150,200.00 per year, depending on experience, location, and employer.

What is a deep learning engineer?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What does a deep learning engineer do?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What skills and qualifications does a deep learning engineer need?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

Are deep learning engineers in demand?

Deep learning engineers are in high demand due to the growth of artificial intelligence and machine learning applications across industries such as technology, healthcare, and finance. They typically require skills in neural networks, programming languages like Python, and frameworks such as TensorFlow or PyTorch, with job opportunities increasing as AI adoption expands.

What are popular job titles related to Deep Learning Engineer jobs in Austin, TX?

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What job categories do people searching Deep Learning Engineer jobs in Austin, TX look for?

The top searched job categories for Deep Learning Engineer jobs in Austin, TX are:

What cities near Austin, TX are hiring for Deep Learning Engineer jobs?

Cities near Austin, TX with the most Deep Learning Engineer job openings:

Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Austin, TX as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $114,846 per year, or $55.2 per hour.

Senior Deep Learning Software Engineer, DLSim

Austin, TX

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

$121K - $160K/yr

Full-time

Posted 15 days ago

Key responsibilities

  • Develop simulation backends that enable evaluation of AI workloads across NVIDIA compiler stacks.

  • Improve deep learning compiler kernel code generation and computational graph optimization using modeled scenarios and performance insights.

  • Partner with architects and software teams to evaluate future GPU features and guide silicon and system-level design decisions.

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

The DL Performance Modeling Team's core mission is to deliver full stack simulation infrastructure for deep learning applications across a spectrum of GPUs. We actively collaborate with architecture, software, product, and research teams to shape and refine the strategic roadmap of DL hardware and software We are now looking for a Deep Learning Software Engineer to help develop simulation infrastructure. The software rapidly assesses new AI-accelerating GPU hardware and software advancements.

What you'll be doing: Develop simulation backends that enable fast, scalable evaluation of AI workloads across NVIDIA compiler stacks. Improve deep learning compiler kernel code generation and computational graph optimization using analysis based on modeled scenarios and performance insight. Advance the modeling and optimization of datacenter-scale AI workloads and deployment scenarios.

Partner with architects and software teams to evaluate future GPU features and guide silicon and system-level design decisions. What we need to see: A Masters (or equivalent experience) in Computer Science, Computer Engineering, or a related STEM field; PhD preferred. 3+ years of relevant experience in compiler optimization, architectural simulation, or related areas.

Strong hands-on experience with MLIR and compiler infrastructure. Excellent C/C++ and Python programming skills, including software design, debugging, performance analysis, and test development. Strong communication and collaboration skills, with the ability to thrive in a fast-paced, multi-functional, outcome-focused environment.

Ways to stand out from the crowd: Experience designing and building compiler frameworks or intermediate representations from the ground up. Deep understanding of LLM inference workloads and their implications for computer architecture. Hands-on experience implementing and optimizing complex AI workloads on CPUs, GPUs, or custom accelerators.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, collaborative and love a challenge, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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