Machine Learning Researcher
Vor 5 Tagen
**Here's the tl;dr**:
- ** We are on a mission** to make programming biology easy. We provide biologists with the software, machine learning & services to discover, design and optimise enzymes and their cell-factories to ultimately produce almost anything.
- We're an **experienced team**. We have built many successful products before and we've raised EUR 5.5m from top tier investors
- We're focused on building the **best possible team culture**. We're distributed across two locations, do almost everything async and are super flexible about when and where we work.
- We offer **top of the market** salary, a generous equity stake in the company and a wide range of benefits from health and wellbeing, financial, to training and career progression opportunities.
**This is Cradle**:
Cradle helps teams to engineer proteins with fewer, more successful experiments. We use generative machine learning models, accessible through user-friendly software interfaces, to help engineer protein properties such as stability, expression, activity, binding affinity and specificity. We are bridge builders who bring together the best of machine learning, synthetic biology, developer tools, and user experience design. Our mission is to enable a world where most of the products around us can be easily made and degraded biologically using a cell-factory instead of (petro-)chemicals, plants or animal agriculture.
**TL;DR**: This is an exceptional opportunity to join a very early stage company reimagining protein design through a computational
- and AI-first approach. If you’re an ML Researcher with experience in the field of large language models applied to protein design, this may be for you.
**Meet Cradle**:
Cradle is an AI startup with a mission to help biologists design improved proteins in record time using powerful prediction algorithms and AI design suggestions. We combine classical bioinformatics tools with cutting edge machine learning models developed and trained in-house using data form our own wet lab as well as data assayed by our design partners.
We are assembling an elite, diverse and highly-skilled team combining the best of machine learning, synthetic biology, developer tools and user experience design to accelerate the process of protein discovery and design. As the first research scientist at this groundbreaking company, you will play an essential role in building the team, and in inspiring and influencing the company culture.
**Position summary**:
**Responsibilities**:
As a machine learning researcher, you will be responsible to:
- Develop an intuition for promising projects and propose ml-based approaches to bring on next
- Build industry relevant benchmarks and validations techniques for models trained on biological data
- Mentor junior Machine Learning engineers
- Collaborate closely with biologists, software engineers and scientists alike and learn to improve the design-build-test-learn loop
- Present scientific findings in journals, conferences, blog posts, etc.
**Need to have (technical)**:
- PhD in Computer Science, Mathematics, Physics, Computational Biology or a related discipline.
- Demonstrated ability to deliver deep learning models to production use.
**Need to have (non-technical)**:
- You are productive by yourself. You will be asked to solve abstract tasks independently and produce results and organize your work without constant supervision.
- You want to grow. Cradle is a high-growth company providing a lot of new opportunities. You enjoy taking on challenging projects and are able to process honest feedback.
- You are able to communicate well. We are working at the intersection of biology and software where good communication is key.
- You are kind and work well in teams. We look for team players who contribute to a positive and friendly working environment.
**Nice to haves**:
- Understand the biological problem a model is designed for and know where its weaknesses lie.
- We are setting up a highly automated ML model provisioning system. Experience with popular machine learning, pipelining and deployment libraries will be of high value.
- You have an understanding of genomics and molecular biology.
**Learn More & Apply**:
Send along links that best showcase the relevant things you've built and done. Ask your favourite person to include a letter on what you mean to them. Feel free to get creative
**Even if you don't meet all the qualifications, but are enthusiastic about the job, we would love to meet you We believe that anyone who is interested in a topic is able to learn. Do not hesitate to apply.
We also strongly encourage people from underrepresented groups to apply.
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