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Nvidia Deep Learning Jobs in Texas (NOW HIRING)

Nvidia

Senior Compiler Engineer - DL

Austin, TX · On-site

$103K - $142K/yr

NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling ...

Nvidia

Senior DL Compiler Engineer -CUDA Tile

Austin, TX

$121K - $160K/yr

NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image ...

Nvidia

Senior DL Compiler Engineer -CUDA Tile

Austin, TX

$121K - $160K/yr

NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image ...

Nvidia

Senior Software Engineer, CUTLASS Platform

Austin, TX · On-site

$121K - $160K/yr

Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs. If you are ...

Nvidia

Backend Compiler Engineer

Austin, TX

... NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited ...

Nvidia

High Performance AI Engineer

Austin, TX

Strong experience in building/evaluating deep learning models, coding agents and developer tooling ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

Nvidia Corporation

Backend Compiler Engineer

Austin, TX · On-site

... NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited ...

Nvidia

Senior LLVM Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

Familiarity with deep learning frameworks and performancecritical workloads on NVIDIA GPUs With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one ...

Nvidia

Senior Developer Technology Engineer - AI

Austin, TX · Hybrid

$54 - $71.25/hr

Expertise in parallelization and performance optimization of Deep Learning models arising from ... NVIDIA's success in the advancement and availability of Artificial Intelligence has created ...

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Nvidia Deep Learning information

What is an Nvidia Deep Learning job?

An Nvidia Deep Learning job typically involves working with AI, machine learning, and deep learning technologies to develop, optimize, and deploy neural network models. Employees in these roles may work on GPU acceleration, AI frameworks like TensorFlow and PyTorch, and specialized hardware like NVIDIA GPUs and TensorRT. Positions can range from research scientists and software engineers to AI infrastructure specialists, focusing on improving model performance and scalability. These professionals contribute to cutting-edge AI applications in fields like autonomous vehicles, healthcare, and robotics.

What are the main challenges faced by professionals working in Nvidia Deep Learning roles?

Professionals in Nvidia Deep Learning positions often encounter challenges such as optimizing deep learning models to run efficiently on GPU architectures, keeping up with rapidly evolving AI frameworks, and troubleshooting complex system-level integration issues. They may also need to balance tight project deadlines with the demands of rigorous research and experimentation. Collaboration with interdisciplinary teams—such as software developers, data scientists, and hardware engineers—is common and essential to deliver robust solutions. Overcoming these challenges helps professionals stay at the forefront of innovation in the AI and deep learning industry.

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

Excelling in an Nvidia Deep Learning role requires a strong background in computer science, machine learning, and mathematics, often supported by an advanced degree in a related field. Expertise in deep learning frameworks (such as TensorFlow or PyTorch), CUDA programming, and experience with Nvidia GPU hardware are typically expected, along with relevant certifications like Nvidia Deep Learning Institute credentials. Strong analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this position. These skills are crucial to efficiently develop, optimize, and deploy deep learning models leveraging Nvidia technologies in cutting-edge applications.

What are popular job titles related to Nvidia Deep Learning jobs in Texas? For Nvidia Deep Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Nvidia Deep Learning jobs in Texas look for? The top searched job categories for Nvidia Deep Learning jobs in Texas are:
Nvidia Deep Learning jobs near you
Infographic showing various Nvidia Deep Learning 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.
Full time: Sr Data Scientist || Fort Worth, TX - Hybrid || **LOCALs Only // No H.1s, No C.2.C

Full time: Sr Data Scientist || Fort Worth, TX - Hybrid || **LOCALs Only // No H.1s, No C.2.C

Prudent Technologies and Consulting, Inc.

Fort Worth, TX • On-site

Other

Posted 2 days ago

Job description

Role: Senior Data Scientist

Type: Full-time/Direct Hire

Location: Fort Worth, TX - Hybrid

Onsite T, W, Th (Local candidates are strongly preferred)


Experience Required: 7+ years of professional Data Science / Applied ML experience


Summary:

Prudent Consulting is seeking a Senior Data Scientist to design, train, and deploy machine learning models on Dell AI Factory (Dell + NVIDIA) infrastructure. Working closely with data engineering, this role will leverage the centralized data warehouse to build production-grade ML solutions that drive measurable business outcomes. The ideal candidate brings deep applied ML expertise combined with hands-on experience in GPU-accelerated model development and deployment.


Required:

  • 7+ years of hands-on experience in data science, applied machine learning, or advanced analytics roles.
  • Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
  • Direct, hands-on experience building and deploying models on Dell AI Factory / NVIDIA AI Enterprise GPU-accelerated infrastructure — required.
  • Strong foundation in statistics, machine learning algorithms, and model evaluation techniques.
  • Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, model registries, CI/CD for ML).
  • Experience working with large-scale structured and unstructured datasets sourced from enterprise data warehouses.


Preferred Skills:

  • Health sciences domain experience - clinical research, healthcare analytics, life sciences, or pharma ML applications
  • Experience with NVIDIA RAPIDS for accelerated data science workflows.
  • Experience with NVIDIA NeMo or Triton Inference Server for model development and deployment.
  • Experience with generative AI / LLM fine-tuning and deployment on NVIDIA infrastructure.
  • NVIDIA Deep Learning Institute (DLI) or Dell AI technology certifications.


Education:

Master's or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field

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