HPC Architect

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