Software Engineer (Machine Learning Research Engineering), London
We are looking for engineers with different levels of experience - Mid through to Senior, Principal, Staff or equivalent levels.
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.
Working in a highly creative, iterative environment, you will be partnering with leading engineers, scientists and ML researchers to build the critical platform driving that transformation. This is a newly created role and you will need to use your previous experience and show initiative in order to fully carve out your contribution.
What you will do
- Partner with the ML Research, Drug Design, and Data Engineering teams to design, develop, train, and evaluate a variety of cutting edge ML models at unprecedented scale.
- Build a world-class ML drug design research environment with scalable software and libraries.
- Develop tools and libraries to enable large-scale machine learning experiments across thousands of accelerators.
- Maximise model performance, scalability, and robustness for production use within our computational platform.
- Create novel instrumental drug discovery tools in partnership with domain experts. Take end-to-end ownership from rapid prototyping to production-quality code.
- Iterate collaboratively with scientists and domain experts to deeply understand feature requirements and user feedback.
Skills and qualifications
Essential
- Strong experience with developing large-scale machine learning models.
- Extensive programming experience using any mainstream programming languages, including strong Python experience.
- Experience with modern ML frameworks including at least one of JAX, PyTorch or TensorFlow.
- Experience with the full ML research and development lifecycle.
- Experience partnering with research and product teams to prototype and ideally productionise ML models.
- Strong software engineering experience with software design / architecture skills.
- Strong understanding of ML theory and applications.
- Strong understanding of data structures and algorithms.
- Either a Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
Nice to have
- Interest in chemistry and biology.
- Experience working with biomedical data.
- Knowledge of the pharmaceutical industry, ideally with a focus on drug discovery.
- Experience developing user facing production code.
Culture and values
What does it take to be successful at IsoLabs? It's not about finding people who think and act in the same way, but we do have some shared values:
Thoughtful
Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day.
Brave
Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.
Determined
Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we.
Together
Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.
Creating an inclusive company
We realise that to be successful we need our teams to reflect and represent the populations we are striving to serve. We’re working to build a supportive and inclusive environment where collaboration is encouraged and learning is shared. We value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact.
We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Hybrid working
It’s hugely important for us to be able to share knowledge and establish relationships with each other, and we find it easier to do this if we spend time together in person. This is why we’ve decided to follow a hybrid model, and for full time positions we would require you to be able to come into the office 3 days a week (currently Tue, Wed, and one other day depending on which team you’re in). For part time positions this may vary. 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.
Please note that when you submit an application, your data will be processed in line with our privacy policy.
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Top Skills
What We Do
Isomorphic Labs is a new Alphabet company and commercial venture which aims to reimagine the entire drug discovery process from first principles with an AI-first approach, and, ultimately, to model and understand some of the fundamental mechanisms of life. Using computational advances, we’re working at the cutting edge in the new era of ‘digital biology’. By significantly increasing the pace of scientific research and efficacy of new medicines, we will be at the forefront of breakthroughs that will benefit millions of people.
