High-Performance Computing

Our client, a market leader in high-performance computing and scientific software, is seeking a HPC Software Architect with strong experience in HPC software architecture and technical leadership. This position offers the chance to shape cutting-edge tools and methods used in large-scale simulations and advanced research, while collaborating with international experts across mathematics, computer science, and physics.

Required Skills & Experience

• MSc, engineering degree, or PhD in computer science, computational science, or a closely related discipline.

• At least five years’ experience in software development, with three years in a technical lead or architect role.

• Strong background in scientific computing, HPC, or large-scale software projects.

• Proficient in multiple programming languages, ideally including Python, C/C++, or Fortran.

• Solid knowledge of parallel programming paradigms (GPU computing, multi-threading, distributed systems).

• Skilled with modern collaborative development tools: Git/GitHub, CMake, Docker, Spack, GTest, CTest, etc.

• Strong communication and teamwork skills, with enthusiasm for interdisciplinary collaborations across applied mathematics, computer science, and physics.

• Excellent written and spoken communication skills 

Key Responsibilities

• Apply your expertise to developing advanced computational patterns, adaptive mesh refinement, particle-based simulations, and related methods.

• Collaborate with research partners to define representative software application that capture the technical complexities of real-world scientific workloads.

• Design modular software architectures that maximize reuse of community frameworks, libraries, and tools, ensuring consistent performance and integration across projects.

• Reduce technical debt and prepare systems for long-term sustainability through proactive refactoring and forward-thinking design.

• Lead the development and integration of mini-applications while mentoring junior engineers and fostering best practices.

• Enhance performance and portability by leveraging advanced parallel programming models (e.g., GPU acceleration, multi-threading) and effective abstraction layers.

• Develop benchmarks and performance metrics to measure scalability, efficiency, and portability.

• Facilitate knowledge transfer through training, documentation, and direct support.

• Contribute actively to Agile project workflows, including planning, retrospectives, demos, and inter-team coordination.