Senior ML Ops Engineer

About Isomorphic Labs

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. 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. We believe 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.

Your Impact

This is an exciting opportunity for you to work on a greenfield ML-based software platform that will transform the biopharmaceutical world. You will join our ML Platform group, partnering with leading engineers, scientists, and ML researchers to build the critical platform driving that transformation. You'll be working as part of a small and highly efficient team on all parts of the ML Model Lifecycle – from infrastructure to software engineering to user experience. We will encourage you to dream up and build the ML platform you wished was already available. Your tools will have access to a large fleet of compute, and your work will be used by some of the best chemistry/biology/ML minds in the world.

What You Will Do

• Build ecosystem and tools to enable cutting-edge ML research and serve large-scale ML models at the forefront of science.
• Build and operate processes and tools for effective operational management of research and production software.
• Design, implement, and manage cloud infrastructure for all stages of ML model lifecycle, from research, through training, to production inference.
• Partner and collaborate with a diverse set of teams including 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:

• Hands-on experience managing and deploying workloads on Kubernetes.
• Experience building and prototyping secure/scalable platforms/products on cloud.
• Strong experience in DevOps best practices.
• Strong foundations in software engineering.
• Proficiency in any of the following: Python, Golang, Rust, JavaScript.

Ideally you’ll also have:

• Experience, and active participation at any stage of the ML Model Lifecycle, for instance:
  • Developing training/inference platforms.
  • Managing large fleets of compute for ML purposes.
  • Or other relevant experience related to ML model lifecycle.
• Practical experience with modern Machine Learning Ops lifecycle, tools, and frameworks.

Nice to have:

• Experience supporting machine learning research activities.
• Familiarity with python-based ML frameworks like TensorFlow, PyTorch, or JAX.
• Experience with Google Cloud Platform (GCP).

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).