Machine Learning Engineer
GTN - A Quantum Leap in Drug Discovery.
Bringing a single new drug to the market costs $2.9bn and takes 15 years, with a high chance of failure. At GTN we combine machine learning and quantum physics, using our unique patent-pending technology, Generative Tensorial Networks, to efficiently access the full drug-like space, i.e. 1060, and to more accurately predict chemical activities. This has the potential to create substantial efficiencies in the whole drug development cycle which could have a huge positive impact on lives globally.
GTN is well funded by Tier-1 VCs and has built an outstanding interdisciplinary team, a world-class board of advisors and collaborations with a number of global pharmaceutical companies and world-leading research institutes.
GTN received the CogX UK Rising Star award for Outstanding Achievement in Machine Learning handed to us by the British Prime Minister, Theresa May and was recently featured in WIRED Magazine.
We are looking for an outstanding Machine Learning Engineer with an adaptable and productive working style which fits in a fast-moving biotech startup. As a Machine Learning Engineer you will run experiments, optimise algorithms and productionise & implement state of the art machine learning models. The team is pioneering in drug discovery, using machine learning and quantum physics so you will work with Research Scientists to bring latest techniques to our platform.
As part of the role you will:
- Implement, evaluate and optimise algorithms and models into our platform.
- Architect and implement software libraries.
- Provide software design and programming support to research projects.
- Implement model testing frameworks and tools that accelerate the research and development cycle.
As part of an ambitious, fast-paced and interdisciplinary team working on tough but impactful challenges, you can expect to work in a collaborative and intellectually fulfilling environment, working on problems that really matter.
- Challenge the norm.
- Agile, pragmatic perseverance.
- Approachable and supportive people.
- Evidenced impact orientation.
- Personal growth.
What we expect:
- Experience of deep learning, reinforcement learning and active learning.
- Masters degree in computer science.
- Strong knowledge and experience of Python.
- Strong knowledge of algorithm design.
- Experience with implementing numerical methods and data visualisation.
- Experience with building end-to-end ML solutions.
- Experience working on complex projects that include: application development, distributed and parallel systems, machine learning, commercial and developing large software systems.
- Experience in probabilistic bayesian learning, and/or semi-supervised/multitask learning
- Experience of optimisation.
- Experience of software development lifecycle.
- Talented, motivated and interesting co-workers.
- Intellectual challenge solving meaningful problems.
- Budget to buy the IT set-up you need.
- Competitive compensation including equity.