ML Ops Engineer, London

ML Ops Engineer, London 

Isomorphic Labs is a new Alphabet company that is reimagining drug discovery through a computational- and AI-first approach.

We are on a mission to accelerate the speed, increase the efficacy and lower the cost of drug discovery. You'll be working at the cutting edge of the new era of 'digital biology' to deliver a transformative social impact for the benefit of millions of people. 

Come and be part of a multi-disciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring, collaborative and entrepreneurial culture.

Your impact 

This is an exciting opportunity for you to work on a greenfield ML-based software platform that will transform the biopharmaceutical world as we know it. 

You will join our Core Engineering group, where you will be 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 working on all parts of 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. Your work will be used by some of the best chemistry/biology/ML minds in the world. You'll be free to pursue the team goals in the best way you see fit. We're interested in you telling us how to build things better.

We believe Isomorphic is best of both worlds: a dynamic startup where things happen fast with the additional benefits that come from Alphabet backing and a long-term vision.

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 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:

• 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)