1

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

GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve ... MS or PhD in a relevant field (Computer Science, Electrical Engineering, Computer Engineering, etc ...

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 ...

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 ...

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

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 ...

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 ...

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer ... Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ...

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

Design, implement, and refine deep learning models to ensure efficiency, scalability, and ... Senior+ engineers will establish standards and tooling that scale across the organization. • ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ...

next page

Showing results 1-20

Deep Learning Engineer information

See Austin, TX salary details

$37.7K

$114.8K

$189.8K

How much do deep learning engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for deep learning engineer in Austin, TX is $114,819.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,200.00 and $150,100.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

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 are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

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.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

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 cities near Austin, TX are hiring for Deep Learning Engineer jobs? Cities near Austin, TX with the most Deep Learning Engineer job openings:
Senior Deep Learning Communication Architect

Senior Deep Learning Communication Architect

Nvidia

Austin, TX • On-site

Full-time

Posted 18 days ago


Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What You'll Be Doing:

  • The software architecture group at NVIDIA has openings for a Deep Learning Communication Architect. We scale the DNN models and training/inference frameworks to systems with hundreds of thousands of nodes.

  • Optimizing communication performance: Identify and eliminate bottlenecks in data transfer and synchronization during distributed deep learning training and inference.

  • Designing efficient communication protocols: Develop and implement communication algorithms and protocols tailored for deep learning workloads, minimizing communication overhead and latency.

  • Hardware and software co-craft: Collaborate with hardware and software teams to craft systems that effectively apply high-speed interconnects (e.g., NVLink, InfiniBand, SPC-X) and communication libraries (e.g., MPI, NCCL, UCX, UCC, NVSHMEM).

  • Exploring innovative communication technologies: Research and evaluate new communication technologies and techniques to enhance the performance and scalability of deep learning systems.

  • Developing and implementing solutions: Build proofs-of-concept, conduct experiments, and perform quantitative modeling to validate and deploy new communication strategies.

What We Need to See:

  • A Ph.D., Masters, or BS in Computer Science (CS), Electrical Engineering (EE), Computer Science and Electrical Engineering (CSEE), or a closely related field or equivalent experience.

  • 6+ years of experience in Building DNNs, Scaling of DNNs, Parallelism of DNN frameworks, or deep learning training and inference workloads.

  • Experience in evaluating, analyzing, and optimizing LLM training and inference performance of state-of-the-art models on cutting-edge hardware.

  • Deep understanding of parallelism techniques, including Data Parallelism, Pipeline Parallelism, Tensor Parallelism, Expert Parallelism, and FSDP.

  • Understanding of the emerging serving architectures like Disaggregated Serving and inference servers like Dynamo and Triton

  • Proficiency in developing code for one or more deep neural network (DNN) training and Inference frameworks, such as PyTorch, TensorRT-LLM, vLLM, SGLang.

  • Strong programming skills in C++ and Python.

  • Familiarity with GPU computing, including CUDA and OpenCL, and familiarity with InfiniBand and RoCE networks. CUDA and OpenCL, and familiarity with InfiniBand and RoCE networks.

Ways to Stand Out from the Crowd:

  • Prior contributions to one or more DNN training and Inference frameworks as part of your previous work experience.

  • Deep understanding and contributions to the scaling of LLMs on large-scale systems.

With competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most hard-working and talented people in the world working for us. If you're creative and passionate about developing cloud services 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 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 24, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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

Year founded

1993