HPC Applications Engineer

Role: HPC Applications Engineer

Location: Gothenburg, Sweden

Hybrid: 2 days a week

Key Accountabilities

· Develop, deliver and operate research computing services and applications.

· Take a Site Reliability Engineering approach to HPC services, managing the

development deployment, monitoring and incident response end-to-end.

· Solve complex technical problems, both with SCP applications and services and

the user’s use of them

· Provide deep research software engineering expertise to assist users in debugging

and optimising their workflows and applications

· Essential Knowledge, Skills, and Experience

· Scientific application installation, optimisation and configuration

· Effective use of HPC job schedulers such as SLURM

· Experienced working in a Linux environment

· Competent in multiple programming and scripting languages from the following

list: python, R, Shell Scripts, C/C++, Golang, and deep expertise in at least one of

them

· Deep understanding of the factors influencing HPC application performance

· Highly customer focused; able to explain IT technical concepts in a manner which

non-IT experts can understand

Required Skills and Knowledge

· Scientific degree, and/or experience in computationally intensive analysis of

scientific data

· Previous experience in high performance computing (HPC) environments,

especially at large scales (>10,000 cores)

· Experience with high performance parallel filesystems at petabyte scale, e.g.

GPFS, Lustre

· Hands-on knowledge of a range of scientific and HPC applications such as

simulation software, bioinformatics tools or 3D data visualisation packages

· Experience with software build frameworks such as Easybuild or Spack

· Expertise in GPU, AI/ML tools and frameworks (CUDA, TensorFlow, PyTorch)

· Strong understanding of parallel programming techniques (e.g. MPI, pthreads,

OpenMP) and code profiling/optimisation

· Experience with workflow engines (e.g. Apache Airflow, Nextflow, Cromwell, AWS

StepFunctions)

· Familiarity with container runtimes such as Docker, Singularity or enroot

· Expertise in specific scientific domains relevant to early drug development, such

as deep learning, medical imaging, molecular dynamics or 'omics.

· Experience with frameworks for regression tests and benchmarks for HPC

applications, like Reframe HPC

· Experience with working in GxP-validated environments

Plus some of the following areas of experience:

· Experience administering and optimising a HPC job scheduler (e.g. SLURM)

· Experience with configuration automation and infrastructure as code (e.g.

Ansible, Hashicorp Terraform, AWS CloudFormation, Amazon Cloud Developer

Kit)

· Experience deploying infrastructure and code to public cloud, especially AWS

· Hands-on experience working in a DevOps team and using agile methodologies