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

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

The Senior Reinforcement Learning Engineer will focus on achieving state-of-the-art performance on ... Required : • Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX ...

Understanding of machine learning and deep learning fundamentals * Develop internal tooling as ... Support infrastructure engineering, security engineering, and architecture * Willing to learn and ...

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

The Senior Reinforcement Learning Engineer will leverage their expertise in reinforcement learning ... Required : • Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX ...

Showing results 41-60

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 Aug 14, 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 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.

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

For Deep Learning Engineer jobs in Austin, TX, the most frequently searched job titles 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:

Infographic showing various Deep Learning Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $114,846 per year, or $55.2 per hour.

Principal Deep Learning Communication Architect

Nvidia

Austin, TX

Full-time

Re-posted 2 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies


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:

  • Architecture Leadership:Define the long-term technical roadmap for communication libraries across NVIDIA's next-generation platforms. You will ensure the seamless scaling of models to clusters comprising hundreds of thousands of nodes.

  • AI Communication Library Design:Lead the development of next-generation communication primitives and collective algorithms. This includes optimizing for heterogeneous interconnects such as NVLink, Spectrum-X (Ethernet), and Quantum-X (InfiniBand).

  • Application- Communication Library Co-Design:Partner with application developers to architect and implement specialized communication primitives. You will ensure that AI and HPC libraries-includingNCCL, NIXL, NVSHMEM, UCC, and UCX-evolve to meet the requirements of trillion-parameter and Agentic AI.

  • Hardware/Software Co-Design:Collaborate with silicon Aarchitects and software engineers to influence hardware specifications for next-generation networking, ensuring they meet the evolving demands of trillion-parameter LLMs and Agentic AI.

  • Quantitative Modeling:Develop high-fidelity analytical models and simulators to predict system behavior under emerging workloads.

What We Need to See:

  • Ph.D. or M.S. in Computer Science, Electrical Engineering, or a related field (or equivalent experience), with 12+ years of industry experience in high-performance computing (HPC) or distributed deep learning.

  • Parallelism Expertise:Deep understanding of 3D parallelism (Data, Tensor, Pipeline) and advanced strategies including Context Parallelism, Expert Parallelism, and Zero Redundancy Optimizer (ZeRO) variants.

  • Technical Proficiency:Deep technical proficiency with NCCL, UCX, UCC, NVSHMEM, or MPI. Experience with RDMA, RoCE, and low-level InfiniBand verbs is required.

  • Inference & Serving:Advanced knowledge of high-throughput inference engines and schedulers, specifically TensorRT-LLM, vLLM, SGLang, and NVIDIA Dynamo.

  • GPU Architecture:Expert knowledge of the NVIDIA GPU memory hierarchy (HBM3e/HBM4, L2 cache) and CUDA programming models.

Ways to Stand Out from the Crowd:

  • Framework Development:Hands-on experience developing within Megatron-Core, DeepSpeed, or JAX/XLA, with an understanding of how these frameworks interact with low-level communication runtimes is a plus.

  • Significant upstream contributions to major open-source projects (e.g., PyTorch Distributed, KServe, or Ray).

  • A proven track record of deploying and optimizing models on NVIDIA platforms or similar rack-scale systems.

  • A strong portfolio of patents or papers in top-tier systems/architecture venues (e.g., ISCA, ASPLOS, NeurIPS, SC).

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 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 18, 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.

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

Year founded

1993