Join AstraZeneca: HPC Applications Engineer Opportunity

AstraZeneca is a global, innovation-driven biopharmaceutical business dedicated to the discovery, development, and commercialization of prescription medicines targeting some of the world’s most serious diseases. More than just a leading pharmaceutical company, AstraZeneca boasts a unique workplace culture that fosters innovation and collaboration. Here, employees are empowered to share diverse perspectives and feel valued, energized, and rewarded for their creativity.

Why Work with Us?

AstraZeneca recognizes the importance of individualized flexibility. Our working model allows employees to balance personal and work commitments while maintaining a strong culture of collaboration and teamwork. At our head office and BlueSky Hub in downtown Toronto, we have designed spaces that promote strategy, brainstorming, and connection on key projects.

Our commitment to sustainability is integral to our culture, recognizing the interconnectedness of people’s health, the planet, and our business. We are taking ambitious actions to address significant challenges of our times, from climate change to healthcare access and disease prevention.

About Our Research Data and Analytics Team

The Research Data & Analytics Team within R&D IT at AstraZeneca is a global collective of experienced, skilled data and AI engineers. Our mission is to transform R&D by leveraging data, analytics, and AI, partnering with scientific teams to expedite the development of safe, effective medicines.

Scientific Computing Platform (SCP)

The SCP is a foundational capability for high-performance computing (HPC) and scaled research computing solutions. It plays a central role in supporting analytics products in computational chemistry, imaging, multi-OMICs, structural biology, data science, and AI. Our team ensures the delivery of high-performance analytics products, blending modern HPC with a sophisticated DevOps stack and cloud-native technologies.

About the Platform

The SCP team offers a high-performance computing platform and optimized applications for scientific workflows, striving to accelerate scientific discovery. This is achieved through the rapid deployment of applications, optimizing complex workflows, and fine-tuning applications for extensive problems. Our overarching principle is maximizing the impact of our support efforts.

Position: HPC Applications Engineer

We seek a passionate HPC engineer with expertise in applications and research software engineering. The ideal candidate possesses extensive hands-on experience with HPC technology, delivering high-quality HPC services, and can effectively communicate with the scientific community to optimize the use of research computing services.

Key Accountabilities:

• Develop, deliver, and operate research computing services and applications.
• Adopt a Site Reliability Engineering approach to manage development, deployment, monitoring, and incident response.
• Solve complex technical problems related to SCP applications and user interactions.
• Provide in-depth research software engineering expertise for debugging and optimization of workflows and applications.

Essential Knowledge, Skills, and Experience:

• Expertise in scientific application installation, optimization, and configuration.
• Effective use of HPC job schedulers such as SLURM.
• Proficiency in a Linux environment.
• Competence in multiple programming and scripting languages like Python, R, Shell Scripts, C/C++, and Golang, with deep expertise in at least one.
• In-depth understanding of HPC application performance factors.
• Customer-focused, capable of explaining technical concepts to non-experts.

Desirable Skills and Knowledge:

• Scientific degree or experience in computationally intensive scientific data analysis.
• Experience with large-scale HPC environments (10,000+ cores).
• Familiarity with high-performance parallel filesystems (e.g., GPFS, Lustre).
• Hands-on knowledge of HPC applications like simulation software, bioinformatics tools, or 3D data visualization.
• Experience with software build frameworks (e.g., Easybuild, Spack).
• Expertise in GPU, AI/ML tools and frameworks (e.g., CUDA, TensorFlow, PyTorch).
• Understanding of parallel programming techniques (e.g., MPI, pthreads, OpenMP).
• Experience with workflow engines (e.g., Apache Airflow, Nextflow).
• Familiarity with container runtimes (e.g., Docker, Singularity).
• Expertise in scientific domains relevant to early drug development.