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Gpu Programming Jobs in Miami, FL (NOW HIRING)

Senior Storage Engineer

Miami, FL · On-site

$120 - $150/hr

We connect AI Factories - high-performance GPU data centers - with the teams that depend on them: research labs training foundation models, enterprises running production inference, and developer ...

Senior Storage Engineer

Miami, FL · On-site

$120 - $150/hr

We connect AI Factories - high-performance GPU data centers - with the teams that depend on them: research labs training foundation models, enterprises running production inference, and developer ...

Service Engineer

Miami, FL · On-site

$79K - $87K/yr

... GPU-related issues (ECC errors, thermal throttling, driver mismatches). • Coordinate RMA and ... Engineering, Electrical Engineering, or equivalent work experience preferred • 1+ years ...

The ideal candidate is a hands-on technology leader with deep experience in infrastructure, servers, multi-GPU environments, and scaling complex engineering initiatives. Blockchain experience is a ...

Data Center Technician

Miami, FL · On-site

$30 - $36/hr

About Introl Introl stands apart as a leader in GPU infrastructure deployments, specializing in ... Our network of 1,000+ field engineers operates globally, tackling the most complex deployments in ...

Role Overview We are looking for a Managing Director, EdgeUno Compute, to lead and scale our GPU ... Collaborate with engineering, operations, and product teams to ensure technical execution aligns ...

Role Overview We are looking for a Managing Director, EdgeUno Compute, to lead and scale our GPU ... Collaborate with engineering, operations, and product teams to ensure technical execution aligns ...

Role Overview We are looking for a Managing Director, EdgeUno Compute, to lead and scale our GPU ... engineering, operations, and product teams to ensure technical execution aligns with business ...

Role Overview We are looking for a Managing Director, EdgeUno Compute, to lead and scale our GPU ... Collaborate with engineering, operations, and product teams to ensure technical execution aligns ...

Senior AI Engineer - SFL Scientific

Miami, FL · On-site

$99K - $137K/yr

SysOps Administrator, DevOps Engineer, Solutions Architect) • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack Company : Deloitte is a business consulting ...

AI & Engineering leverages innovative engineering capabilities to build, deploy, and operate ... Working fluency in AI/ML workload characteristics (training vs. inference), GPU/TPU architectures ...

Senior DevSecOps Engineer

Miami, FL · On-site

$109K - $150K/yr

Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and ... This is a hands-on engineering role that owns our Secure Software Development Lifecycle (SSDLC) end ...

Its Quake AI business delivers AI compute as a service, operating AI data centers including GPU and ... Rumble Cloud is seeking a Senior Platform Engineer (Security) to help operate, secure, and ...

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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 Aug 12, 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 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 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 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:
Infographic showing various Gpu Programming job openings in Miami, FL as of August 2026, with employment types broken down into 83% Full Time, and 17% Temporary. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $62,144 per year, or $29.9 per hour.

Senior Storage Engineer

Hydra Host, Inc.

Miami, FL • On-site

$120 - $150/hr

Other

Posted 6 days ago


Job description

# Senior Storage Engineer at Hydra HostJob Title: Storage Engineer**About Hydra Host**Hydra Host is a Founders Fund-backed NVIDIA cloud partner building the infrastructure platform that powers AI at scale. We connect AI Factories - high-performance GPU data centers - with the teams that depend on them: research labs training foundation models, enterprises running production inference, and developer platforms demanding scalable compute capacity. Hydra Host is building the next-generation bare-metal GPU infrastructure network and marketplace under its Brokkr platform. The company enables independent data centers to monetize GPU capacity while providing enterprises with scalable, high-performance access to NVIDIA-based compute (e.g., H100, H200, B200, L40S, RTX 4090). As we expand our infrastructure capabilities, Hydra Host is now seeking a Storage Engineer to lead the architecture, development, and deployment of our next-generation AI/HPC storage platform.**The role:**As a Storage Engineer, you will be responsible for designing and building Hydra Host’s first production-grade storage platform from the ground up, supporting the company’s rapidly expanding network of bare-metal GPU clusters.You’ll own the architecture, technology selection, implementation, and evolution of this platform, defining how Hydra Host manages data for large-scale, distributed AI workloads across global data centers.This is a senior, hands-on role for an engineer who has built storage systems for GPU clusters before, with deep expertise in both block and object storage and a strong understanding of parallel file systems, performance optimization, and large-scale orchestration.**Key Responsibilities**· Define, architect, and implement Hydra Host’s first production storage platform tailored for bare-metal GPU clusters and AI/HPC workloads.· Lead all technical decisions around storage stack design, from hardware infrastructure to parallel file system orchestration and performance tuning.· Select, build, and maintain storage solutions spanning both block (NVMe, SAN, Ceph, etc.) and object storage (S3-compatible, custom, or Ceph Object Gateway) layers.· Design for high-throughput, low-latency access, supporting large datasets, rapid checkpointing, and parallel access for distributed AI training workloads.· Integrate and optimize parallel file systems such as Lustre, BeeGFS, Spectrum Scale, WekaIO, or CephFS, ensuring maximum performance and fault tolerance.· Ensure compatibility across Hydra’s diverse GPU/OEM ecosystem, accounting for unique firmware, BMC/Redfish APIs, and hardware configurations.· Develop automation, observability, and management tooling for storage, focusing on reliability, scalability, and efficiency.· Act as a builder and architect: deeply hands-on in deployment, troubleshooting, and optimization, while guiding long-term storage roadmap.· Collaborate cross-functionally with GPU, HPC, and platform engineering teams to integrate storage with compute and network layers.· Interface with customers and product leadership to define feature priorities, performance benchmarks, and future enhancements.**Must-Have Qualifications**· 8+ years of progressive, hands-on experience designing and implementing high-performance storage systems for compute clusters in HPC, AI, or bare-metal cloud environments.· Proven track record building storage infrastructure from scratch, not just operating existing systems.· Deep expertise in block storage (NVMe, SAN, Ceph, distributed block systems) and object storage (S3, MinIO, Ceph Object Gateway, etc.).· Strong background in parallel file systems (WekaIO, BeeGFS, Lustre, Spectrum Scale, or similar) supporting GPU or AI cluster workloads.· Solid foundation in Linux systems engineering, automation, and scripting for distributed environments.· Familiarity with BMC, Redfish APIs, and OEM server firmware for bare-metal management.· Deep understanding of AI/ML data pipelines: model checkpointing, data locality, and multi-tiered storage optimization.· Excellent problem-solving, debugging, and communication skills, able to translate technical decisions into clear architectural direction.**Preferred Qualifications**· Experience building storage solutions for large-scale GPU or HPC infrastructure.· History of technical leadership or mentorship, growing teams or owning a product roadmap.· Experience evaluating and managing vendor relationships and negotiating storage hardware/software contracts.· Contributions to open-source HPC or storage projects (Ceph, Lustre, BeeGFS, etc.).· Familiarity with confidential computing, secure data handling, or high-availability architectures. #J-18808-Ljbffr