Software Engineer (HPC Platform)

About Iso

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.

Your impact

We are building the largest foundation models in biotech and applying them immediately to cure disease. You will play a key role and work at a grand scale to deliver the foundations that make this happen. By partnering with in-house machine learning experts and biotech researchers you will join a team to efficiently scale and plan the base on which our groundbreaking AI is built.

What you will do

• You will focus on the end-to-end GPU/TPU (accelerator) strategy, designing infrastructure, optimizing performance, and integrating new hardware to leverage advancements. In partnership with our Machine Learning Platform team, regularly work in the environment to push and support deployments. Regularly be building, monitoring and managing cluster deployments.
• Support the technical strategy around hardware acquisition and deployment decisions.
• Drive research and efficiency design around the infrastructure up to the point of service to the ML platforms teams.
• Contribute to the efforts for consistently improving the reliability of our ML runs.
• Operate and handle research, development, and production cloud infrastructure and systems.
• Partner and collaborate with a diverse set of teams incl. science, research, product, business development and operations.
• Contribute to core technical decisions (e.g. choice of tooling, infrastructure, and architectural design).

Skills and qualifications

Essential:

• Possess real world experience of large scale AI/ML workloads.
• Have experience working in cloud compute infrastructure design, preferably GCP.
• Possess strong programmings skills.
• Have significant experience working and deploying in Kubernetes.
• Familiarity with the Nvidia GPU generations.

Nice to have:

• Have a background in either ML SWE or infrastructure SRE work to build on.
• Have experience leading and delivering projects to multidisciplinary stakeholders.
• Familiarity with Google TPU generations.
• Familiarity with: workload scheduling; machine learning efficiency research; familiarity with ML-driven R&D cycles; familiarity with hardware benchmarking.

Hybrid working

It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.