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Remote Hpc Engineer Jobs in Decatur, GA (NOW HIRING)

PRAGMATIKE

CUDA Kernel Engineer

Atlanta, GA · Remote

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... Background in GPU acceleration for ML frameworks or HPC workloads. * Knowledge of model inference ...

Emory University

Post Doctoral Fellow - Dr. Yan Sun

Atlanta, GA · On-site +1

$47.70K - $64.70K/yr

... R/Python programming languages. * Experience with high-performance computing (HPC) environment ... Emory reserves the right to change remote work status with notice to employee. Emory is an equal ...

Emory University

Post Doctoral Fellow - Dr. Yan Sun

Atlanta, GA · On-site +1

$47.70K - $64.70K/yr

... R/Python programming languages. * Experience with high-performance computing (HPC) environment ... Emory reserves the right to change remote work status with notice to employee. Additional Details ...

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Remote Hpc Engineer information

See Decatur, GA salary details

$38.1K

$99.3K

$134.2K

How much do remote hpc engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for remote hpc engineer in Decatur, GA is $99,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,000.00 and $113,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote HPC Engineer, and why are they important?

To thrive as a Remote HPC Engineer, you need a solid background in computer science or engineering, expertise in high-performance computing architectures, and experience with parallel programming. Familiarity with HPC job schedulers (like Slurm), Linux systems, distributed storage, and relevant certifications (such as CompTIA Linux+ or HPC-specific credentials) are commonly required. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for addressing complex technical challenges remotely. These competencies ensure efficient system performance, seamless collaboration, and successful support of computational research or enterprise workloads.

How do Remote HPC Engineers typically collaborate with on-site teams to manage high-performance computing clusters?

Remote HPC Engineers often rely on robust communication tools and version control systems to coordinate with on-site system administrators, researchers, and IT staff. They participate in regular virtual meetings to discuss cluster performance, resolve technical issues, and plan for upgrades or maintenance. Secure remote access protocols allow engineers to monitor, troubleshoot, and configure systems from afar, but effective collaboration also depends on clear documentation and periodic knowledge sharing sessions. Building strong relationships with on-site personnel helps ensure smooth operations and prompt resolution of any hardware or software challenges.

What are Remote HPC Engineers?

Remote HPC (High Performance Computing) Engineers are professionals who design, implement, and manage high-performance computing systems, typically from a remote location. They work with powerful computer clusters and supercomputers to support complex computations in fields like scientific research, engineering, and data analysis. Their responsibilities include configuring hardware and software, optimizing system performance, troubleshooting issues, and ensuring the security and reliability of HPC resources. By working remotely, these engineers can support organizations and research teams around the world without needing to be physically present at the data center.

What is the difference between Remote Hpc Engineer vs Remote Cloud Engineer?

AspectRemote Hpc EngineerRemote Cloud Engineer
Required CredentialsBachelor's in Computer Science or related, certifications like HPC or LinuxBachelor's in Computer Science or related, cloud certifications (AWS, Azure)
Work EnvironmentHigh-performance computing clusters, research labs, data centersCloud platforms, virtual environments, cloud service providers
Employer & Industry UsageResearch institutions, scientific organizations, tech companiesTech firms, startups, enterprises using cloud infrastructure
Common Search & ComparisonYesYes

The main difference between a Remote Hpc Engineer and a Remote Cloud Engineer lies in their focus areas. Hpc Engineers specialize in high-performance computing systems used for scientific and research purposes, while Cloud Engineers focus on designing and managing cloud-based infrastructure. Both roles require technical expertise and certifications, but their work environments and industry applications differ significantly.

What are popular job titles related to Remote Hpc Engineer jobs in Decatur, GA? For Remote Hpc Engineer jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Remote Hpc Engineer jobs in Decatur, GA look for? The top searched job categories for Remote Hpc Engineer jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Remote Hpc Engineer jobs? Cities near Decatur, GA with the most Remote Hpc Engineer job openings:
Remote Hpc Engineer jobs near you

CUDA Kernel Engineer

PRAGMATIKE

Atlanta, GA • Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 27 days ago

Job description

Location: Remote US
Start date: ASAP
Languages: English (required)

About the Role

Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers.

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch. You will work on the GPU performance layer powering large-scale, high-throughput AI systems used by Fortune 500 customers.

This role is ideal for someone who deeply understands NVIDIA GPU architecture, memory hierarchy, warp-level execution, and profiling workflowsnot someone coming from generic hardware, FPGA, or non-NVIDIA compute backgrounds. You will directly influence the GPU efficiency, throughput, and scalability of mission-critical AI systems.

What Youll Do

  • Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs, with a focus on maximizing occupancy, memory throughput, and warp efficiency.
  • Profile GPU workloads using tools such as Nsight Compute, Nsight Systems, nvprof, and CUDA‐MEMCHECK.
  • Analyze and eliminate performance bottlenecks including warp divergence, uncoalesced memory access, register pressure, and PCIe transfer overhead.
  • Improve GPU memory pipelines (global, shared, L2, texture memory) and ensure proper memory coalescing.
  • Collaborate closely with AI systems, model acceleration, and backend distributed systems teams.
  • Contribute to GPU architecture decisions, kernel libraries, and internal performance-engineering best practices.

What Were Looking For

  • Proven track record building NVIDIA CUDA kernels from scratchnot just calling existing libraries.
  • Strong ability to optimize kernels (tiling strategies, occupancy tuning, shared memory design, warp scheduling).
  • Deep understanding of CUDA threads, warps, blocks, and grids, GPU memory hierarchy and memory coalescing, as well as warp divergence (how to detect, analyze, and mitigate it)
  • Experience diagnosing PCIe bottlenecks and optimizing host-device transfers (pinned memory, streams, batching, overlap).
  • Familiarity with C++, CUDA runtime APIs, and GPU debugging/profiling tooling.

Bonus Points

  • Experience with multi-GPU or distributed GPU systems (NCCL, NVLink, MIG).
  • Background in GPU acceleration for ML frameworks or HPC workloads.
  • Knowledge of model inference optimization (TensorRT, CUDA Graphs, CUTLASS).
  • Exposure to compiler-level optimization or PTX/SASS analysis.
  • Startup experience or comfort working in fast-moving, ambiguous environments.

Why This Role Will Pivot Your Career

  • Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions.
  • Customer impact: Deploy AI solutions powering Fortune 500 clients.
  • Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave).
  • Funding & growth: Oversubscribed seed round, next funding in 2026.
  • Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale.
  • Culture & autonomy: Own critical systems while collaborating with world-class engineers.
  • Aspirational impact: Solve GPU/AI performance challenges few engineers ever face.

Benefits

  • Competitive salary & equity options
  • Sign-on bonus
  • Health, Dental, and Vision
  • 401k

Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.