Location Mississauga, Ontario, Canada
Job ID R-223423
Date posted 03/07/2025
At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe.
Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices 3 days a week. Our head office and BlueSky Hub in downtown Toronto are purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects.
Our dedication to sustainability is also central to our culture and part of what makes AstraZeneca a great place to work. We know the health of people, the planet and our business are interconnected which is why we’re taking ambitious action to tackle some of the biggest challenges of our time, from climate change to access to healthcare and disease prevention.

ACCOUNTABILITIES

Embedded within the R&D IT Data & Analytics Team, our innovative environment empowers remarkable advancements in medicine discovery and development. Collaborate with a diverse team of data engineers, AI experts, and computational scientists. Your expertise will facilitate the optimization of scientific workflows, resolve technical challenges, and drive continuous improvements that enable scientists to achieve their research objectives efficiently.

DESIRABLE SKILLS AND KNOWLEDGE

• A scientific degree or experience in computational analysis of scientific data.
• Hands-on expertise with large scale HPC environments and high-performance parallel filesystems.
• Familiarity with GPU, AI/ML tools and frameworks (CUDA, TensorFlow, PyTorch).
• Experience with workflow engines, container technologies, and software build frameworks.
• Understanding of infrastructure as code, cloud deployment (especially AWS), and agile methodologies.
  When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
  At AstraZeneca, we connect across the whole business to power each function to better influence patient outcomes and improve their lives. We play an increasingly crucial role in driving disruptive transformation on our journey to becoming a digital and detailed enterprise. Here, you will work in synergy with leading experts in our specialist communities, bringing together diverse areas and external partners to drive efficiencies that enable us to succeed. Our commitment to innovation meets large scale impact as we turn complex information into life-changing insights every day.
  Ready to make a difference? Apply now to drive advancements in research computing at AstraZeneca!

INTRODUCTION TO ROLE

AstraZeneca is driving the future of biopharmaceuticals with significant investments in our Scientific Computing Platform (SCP). We’re revolutionizing how researchers maximize high performance computing (HPC) to accelerate scientific discovery and enhance patient outcomes. As our High-Performance Compute Engineer focusing on applications, you will be pivotal in advancing this mission by optimizing research workflows and enabling seamless, high quality HPC services.

WHAT YOU’LL DO:

• Lead as a subject matter expert in high-performance computing applications and research software engineering.
• Optimise and operate cutting edge HPC services and applications to solve complex scientific challenges.
• Develop and deploy industry leading research computing services with a focus on automation and DevOps practices.
• Partner with scientific users to optimise their code, ensuring the best use of HPC resources.
• Implement a Site Reliability Engineering approach to lead development, deployment, and monitoring processes effectively.