HPC Development Support Engineer

Role Overview

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Highly skilled HPC professional specialising in NVIDIA GPU development practices, embedded within the customer's development teams. This resident role focuses on supporting application migration and optimization on new HPC infrastructure, acting as a trusted technical advisor and bridge between customer teams and infrastructure partners.

Context

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• Deployment Model: On-site residency Pau within customer's development teams
  
• Infrastructure Focus: New HPC environment with NVIDIA GPU acceleration
  
• Partnership Ecosystem: Collaboration with Dell infrastructure and NVIDIA compiler support teams
  
• Mission: Enable successful application migration, optimization, and long‑term operational excellence
  

Key Responsibilities

Application Migration and Optimization

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• Assist in migrating applications to the new HPC environment, ensuring compatibility and performance
  
• Profile and fine‑tune HPC applications for the production system
  
• Identify performance bottlenecks and optimization opportunities
  
• Ensure applications leverage GPU acceleration effectively
  

Technical Expertise

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• Troubleshoot and resolve issues related to application deployment, platform compatibility, performance optimization, and system integration
  
• Support continuous improvement initiatives for application lifecycle management
  
• Provide hands‑on technical guidance for complex HPC challenges
  

Trusted Advisor Role

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• Provide strategic guidance on development and optimization best practices for HPC environments
  
• Recommend tools, frameworks, and processes to improve scalability and reliability
  
• Share industry best practices and emerging technologies
  
• Mentor customer teams on HPC development methodologies
  

Collaboration and Governance

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• Participate in regular meetings with the customer to review progress and align priorities
  
• Act as a liaison between customer development teams and Dell infrastructure technical experts
  
• Act as a liaison between customer development teams and NVIDIA compiler support
  
• Facilitate knowledge transfer and cross‑team communication
  
• Document technical decisions, recommendations, and lessons learned
  

DevOps Enablement

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• Assist in designing and implementing CI/CD pipelines tailored for HPC applications
  
• Integrate automated testing and deployment workflows
  
• Support DevOps best practices adapted to HPC constraints and requirements
  
• Enable reproducible builds and deployment automation
  

Required Technical Skills
HPC & GPU Development

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• NVIDIA GPU Programming: CUDA, profiling tools (Nsight, nvprof)
  
• HPC Application Optimization: Performance tuning, parallelization strategies
  
• Profiling & Benchmarking: Application performance analysis and optimization
  
• Compiler Expertise: NVIDIA HPC SDK, GPU‑accelerated libraries (cuBLAS, cuFFT, NCCL)
  

Software Development

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• Programming Languages: C/C++, Python, Fortran (asset)
  
• Parallel Programming: MPI, OpenMP, GPU acceleration
  
• Version Control: Git, GitLab/GitHub workflows
  
• Build Systems: CMake, Make, containerization (Docker, Singularity)
  

HPC Infrastructure

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• Linux Systems: Deep knowledge of HPC Linux environments
  
• Job Schedulers: Slurm, PBS, LSF experience
  
• Storage Systems: Parallel file systems (Lustre, GPFS)
  
• Networking: High‑speed interconnects (InfiniBand, RoCE)
  

DevOps & Automation

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• CI/CD Tools: Jenkins, GitLab CI, GitHub Actions
  
• Container Technologies: Docker, Singularity/Apptainer for HPC
  
• Scripting: Bash, Python for automation
  
• Infrastructure as Code: Ansible, Terraform (asset)
  

Required Profile
Essential Experience

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• 5+ years in HPC environments (supercomputing centers, research labs, or industry HPC)
  
• Strong NVIDIA GPU development experience (CUDA programming, optimization)
  
• Application porting and optimization on HPC systems
  
• Profiling and performance analysis expertise
  
• Linux system administration in HPC contexts
  

Technical Competencies

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• Deep understanding of GPU architecture and memory hierarchy
  
• Experience with parallel programming models (MPI, OpenMP, CUDA)
  
• Knowledg