Machine Learning Engineer at Novogaia, Remote, £Contractor Rate

Company Description

At Novogaia, we are accelerating the discovery of natural products from fungi using machine learning and metabolomics analysis. Our mission is to build machine learning models that can rapidly screen the chemical space of fungi and identify novel bioactive small molecules for applications in pharmaceuticals and agriculture.

Role Description

This is a 40h/week, remote role for a Machine Learning Engineer at Novogaia. Working alongside our CTO, David Kubánek, you’ll be helping us build computational models for predicting the properties of molecules produced by fungi based on their DNA and mass spectra.

The role would best suit a machine learning research engineer with previous exposure to computational modeling in biology and chemistry, looking to work in a fast-paced, high-conviction environment with real-world impact.

The starting date of this role is as soon as possible, starting as a contractor. This role can transition to a full-time role as a founding research engineer including stock options (equity).

Responsibilities

• Developing proprietary machine learning algorithms to analyze fungal biochemistry
• Fine-tuning foundational models for downstream prediction tasks
• Running computational experiments and visualizing findings for analysis

Competencies

Core

• Experience with building & fine-tuning ML models in Python (e.g., in PyTorch)
• Experience analyzing large datasets
• Bachelor's degree in Computer Science, Data Science, Statistics, Machine Learning, or a related field
• Thriving in an environment with ambiguity where you can adapt quickly
• Ability to work independently and in a team setting

Nice-to-have

• Experience with self-supervised learning
• Experience with ML models in biology and chemistry (e.g., AlphaFold2, AutoDiff)
• Experience with computational metabolomics
• Experience with collaborative work in cloud environments and high-performance computing
• Drive to learn the basic biochemical mechanisms underpinning our work

Come join us

If you find this exciting and think you'd be a great fit, we’d love to hear from you!