HPC Architect
Camber
Job Description
HPC Architect
San Francisco, California
About Camber
Camber is on a mission to democratize scientific computing from astrophysics to genomics. Currently, distributed scientific workloads are nearly 100% on-premise, making computation for researchers limited in scope, with long iteration cycles. Our fully managed, infrastructure-free platform allows researchers to deploy on-demand fully managed instances for distributed scientific simulations and data analysis. We’re based in San Francisco and backed by top venture capital firms Pear VC and Base 10 Partners.
About The Role
Camber is seeking a visionary, highly motivated science and research computing expert. The HPC Architect is responsible for designing, implementing, and optimizing high-performance computing environments to support complex computational workloads, in our cloud platform. This role combines deep technical expertise with strategic foresight to develop scalable, efficient computing solutions.
Responsibilities
- Design and architect high-performance computing infrastructure, including hardware, software, and network components
- Evaluate and select appropriate technologies to meet performance, scalability, and efficiency requirements
- Develop comprehensive HPC solutions that align with business objectives and research needs
- Collaborate with engineers and scientists to quickly iterate on the optimal solution
- Optimize existing HPC environments for performance, energy efficiency, and cost-effectiveness
- Create detailed documentation of system architecture, configurations, and best practices
- Stay current with emerging HPC technologies, frameworks, and methodologies
- Develop strategies for system monitoring, maintenance, and upgrading
Qualifications:
- Bachelor's degree in Computer Science, Engineering, or related field; advanced degree preferred
- 5+ years of experience in HPC environments, with demonstrated expertise in architecture design
- Strong knowledge of parallel computing, distributed systems, and computational optimization
- Experience with job scheduling systems (e.g., Slurm, PBS, LSF)
- Proficiency in HPC programming models (MPI, OpenMP, CUDA)
- Familiarity with various storage solutions (parallel file systems, object storage)
- Understanding of networking technologies relevant to HPC (InfiniBand, OmniPath, etc.)
- Knowledge of containerization and virtualization in HPC contexts
- Experience with system monitoring and performance analysis tools
- Excellent problem-solving and analytical skills
Benefits
- Competitive salary and meaningful equity
- A flexible vacation policy
- Comprehensive health, vision, dental, and life insurance as well as disability benefits
- Being part of and building out a world-class team
Camber
San Francisco, CA