Senior ML Ops Engineer, London

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 ML Platform 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 believe Isomorphic is best of both worlds: a dynamic startup where things happen fast with a secure Alphabet backing and a long-term vision.

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.

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)

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). As an equal opportunities employer, we are committed to building an equal and inclusive team. 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.