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Gpu Programming Jobs in Miami, FL (NOW HIRING)

2T Consulting

Linux Systems Administrator

Miami, FL · On-site

... and GPU-based computing infrastructure. * Collaborate with research, engineering, infrastructure, and application teams to support computational workloads. * Maintain system documentation ...

2T Consulting

Linux Systems Administrator

Miami, FL · On-site

... and GPU-based computing infrastructure. * Collaborate with research, engineering, infrastructure, and application teams to support computational workloads. * Maintain system documentation ...

2T Consulting

Linux Systems Administrator

Doral, FL · On-site

... and GPU-based computing infrastructure. * Collaborate with research, engineering, infrastructure, and application teams to support computational workloads. * Maintain system documentation ...

2T Consulting

Linux Systems Administrator

Miami, FL · On-site

... and GPU-based computing infrastructure. * Collaborate with research, engineering, infrastructure, and application teams to support computational workloads. * Maintain system documentation ...

2T Consulting

Linux Systems Administrator

Miami, FL · On-site

... and GPU-based computing infrastructure. * Collaborate with research, engineering, infrastructure, and application teams to support computational workloads. * Maintain system documentation ...

2T Consulting

Linux Systems Administrator

Miami, FL · On-site

... and GPU-based computing infrastructure. * Collaborate with research, engineering, infrastructure, and application teams to support computational workloads. * Maintain system documentation ...

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Gpu Programming information

See Miami, FL salary details

$31.6K

$62.1K

$91.3K

How much do gpu programming jobs pay per year?

As of Sep 3, 2026, the average yearly pay for gpu programming in Miami, FL is $62,144.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,300.00 and $76,500.00 per year, depending on experience, location, and employer.

What is GPU programming?

A GPU Programming job involves writing and optimizing code to run on Graphics Processing Units (GPUs) for parallel computing tasks. This role is commonly found in fields like machine learning, scientific computing, gaming, and data analytics. GPU programmers use languages such as CUDA, OpenCL, or Vulkan to accelerate computations and improve performance. They work closely with software engineers and data scientists to optimize algorithms for high-performance applications.

What types of projects or applications do GPU programmers commonly work on?

GPU Programmers are often involved in developing or optimizing software for high-performance applications such as machine learning, scientific simulations, real-time rendering in gaming and visualization, and video/image processing tools. Their daily work may include collaborating with software engineers, data scientists, and hardware teams to create efficient, scalable parallel algorithms that leverage GPU capabilities. The role frequently requires problem-solving to maximize computational efficiency and troubleshooting complex performance bottlenecks. By working across multidisciplinary teams, GPU Programmers help deliver robust solutions for data-intensive problems in areas like healthcare, finance, automotive technology, and entertainment.

What are the key skills and qualifications needed to thrive in GPU programming, and why are they important?

To excel in GPU Programming, you need a strong background in parallel computing concepts, mathematics, and proficiency in languages such as CUDA, OpenCL, or DirectX/OpenGL, often supported by a degree in computer science, engineering, or a related field. Familiarity with NVIDIA and AMD GPU development tools, performance profilers, and possibly certifications like NVIDIA's Deep Learning Institute courses are valuable. Teamwork, effective communication, and strong problem-solving abilities are essential soft skills in this field. These competencies enable efficient development, optimization, and integration of high-performance GPU code in real-world applications.

What are the most commonly searched types of Gpu Programming jobs in Miami, FL?

The most popular types of Gpu Programming jobs in Miami, FL are:

What are popular job titles related to Gpu Programming jobs in Miami, FL?

For Gpu Programming jobs in Miami, FL, the most frequently searched job titles are:

What job categories do people searching Gpu Programming jobs in Miami, FL look for?

The top searched job categories for Gpu Programming jobs in Miami, FL are:

Gpu Programming jobs near you
Infographic showing various Gpu Programming job openings in Miami, FL as of August 2026, with employment types broken down into 1% Internship, 82% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $62,144 per year, or $29.9 per hour.

Linux Systems Administrator

2T Consulting

Coral Gables, FL

Full-time

Posted 9 days ago

Job description

We are seeking a Linux Systems Administrator with experience supporting High-Performance Computing (HPC) environments, AI clusters, and research computing infrastructure. The ideal candidate will have strong Linux administration, cluster management, troubleshooting, and performance-tuning skills. Experience supporting research or scientific computing environments, particularly grant-funded research environments, is highly preferred.

Roles and Responsibilities
  • Administer, maintain, and support Linux server environments across enterprise and HPC infrastructure.
  • Support and maintain HPC and computational computing clusters, ensuring system availability and performance.
  • Install, configure, upgrade, patch, and maintain Linux operating systems, applications, and system software.
  • Support and administer HPC job scheduling environments, preferably Slurm.
  • Monitor system health, resource utilization, performance, and capacity across Linux and HPC environments.
  • Troubleshoot complex operating system, application, networking, storage, and hardware issues.
  • Perform system and application performance tuning to optimize compute workloads.
  • Support storage infrastructure, server hardware, networking, and high-performance computing components.
  • Assist with deployment, configuration, and maintenance of AI and GPU-based computing infrastructure.
  • Collaborate with research, engineering, infrastructure, and application teams to support computational workloads.
  • Maintain system documentation, operational procedures, and technical standards.
  • Support upgrades, migrations, and infrastructure improvements while minimizing service disruption.
  • Identify opportunities to improve system reliability, performance, automation, and operational efficiency.
Required Qualifications
  • Hands-on experience administering Linux server environments.
  • Experience supporting HPC or computational computing clusters.
  • Experience with HPC job schedulers, preferably Slurm.
  • Experience installing, upgrading, patching, configuring, and maintaining Linux systems and applications.
  • Strong knowledge of storage infrastructure, networking, and server hardware.
  • Strong troubleshooting, systems analysis, and performance-tuning skills.
  • Ability to diagnose and resolve complex infrastructure and system-level issues.
Preferred Qualifications
  • Experience supporting AI clusters, GPU infrastructure, or AI-focused computing environments.
  • Experience with parallel file systems.
  • Experience supporting research, scientific, academic, or computational computing environments.
  • Experience supporting grant-funded research infrastructure.
  • Knowledge of SAN, InfiniBand, and high-performance networking technologies.
  • Familiarity with automation, scripting, monitoring, and infrastructure management tools.
  • Experience working in large-scale distributed computing environments.

Apply