Lead Consultant - HPC Application Engineer

Job Description

Job Title: Lead Consultant - HPC Application Engineer

Career Level: E

Introduction to role

Join our dynamic Research Data & Analytics Team within R&D IT, a global group of skilled data and AI engineers dedicated to revolutionizing the way we discover and develop medicine. Our mission is to partner with scientific teams to deliver innovative capabilities, products, and platforms that accelerate the development of safe and effective medicines for patients.

Scientific Computing Platform

The Scientific Computing Platform (SCP) is a key component of our efforts, providing high-performance computing (HPC) solutions that support computational chemistry, imaging, multi-OMICs, structural biology, data science, and AI.

About the Platform

The SCP team provides the high-performance computing (HPC) platform and optimised applications on which scientists build their workflows. We are driven to accelerate scientific discovery, and achieve this through rapid deployment of applications, optimisation of complex workflows and application tuning for very large problems. An overarching principle is to maximise the impact of the team's support efforts.

We are seeking a passionate HPC engineer focussed on applications and research software engineering. The ideal candidate will have extensive hands-on experience making an impact with HPC technology, delivering HPC services to a high quality, and able to relate to the scientific community and work closely with users to make the best use of research computing services.

The HPC landscape is continually evolving. You will need the skills to help build, optimise and operate industry-leading capabilities, including application build frameworks, containerised applications and cloud software-as-a-service. Automated deployment is a key feature of your work and you will need to be comfortable with DevOps processes and delivering consistency through automation and infrastructure-as-code. A strong focus of the role will also be working directly with scientific users to help them optimise and productionise their code and make best use of the facility.

Accountabilities

As an HPC Application Engineer, you will be responsible for developing, delivering, and operating research computing services and applications. You will take a Site Reliability Engineering approach to manage the end-to-end development, deployment, monitoring, and incident response of HPC services. Your role will involve solving complex technical problems related to SCP applications and services, as well as assisting users in debugging and optimizing their workflows and applications. You will work closely with scientific users to help them optimize and productionize their code, ensuring they make the best use of our research computing services.

Essential Skills/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

Desirable Skills/Experience

• 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
• 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

At AstraZeneca, we demonstrate technology to impact patients' lives directly by transforming our ability to develop life-changing medicines. We empower our teams to perform at their peak by combining cutting-edge science with leading digital technology platforms and data. Our dynamic environment encourages innovation and ownership, providing countless opportunities to learn and grow. Join us in our mission to reinvent the industry and make a meaningful impact on the world.

Ready to make a difference? Apply now!

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.