Our mission is to improve the lives of people living with a skin disease.
Imagine develops image recognition-based artificial intelligence to give both patients and doctors a better understanding of the development of skin diseases, improving diagnoses and making it easier to find the right personalised combination of treatment and lifestyle.
Our focus is on chronic diseases such as psoriasis or eczema, where misdiagnosis rates can be as high as 55%, access to dermatologists involves long waiting times, and it often takes years of struggle to get correctly diagnosed and find a way to manage the disease.
Imagine’s complementary apps are used by thousands of patients around the world who track the development of their skin condition and thus provide us with valuable data points. We are a multi-disciplinary team of currently 11 people and as part of the LEO Innovation Lab located in central Copenhagen.
Read more about Imagine and how it is to work in our team here
You have gathered substantial expertise and knowledge in one or multiple deep learning avenues. You’ve encountered the highlights and lowlights, what critic and hype is justified, and now you’re looking to apply all your skills to make a real impact and help people with products building on your research successes. You apply dedication, systems and lateral thinking, and perseverance to your work and you thrive well in a non-hierarchical, collaborative and fast-paced setting where you take initiative and drive outcomes towards the shared goals.
This is a senior position and you will work with a small team on the big challenge to establish AI-powered diagnosis or severity assessment capabilities with sensitivity and specificity towards the 90s. Working closely with others with machine learning, computer vision and also product, business and medical background, your core tasks will include to:
- Define, implement, test and iterate on deep learning approaches to reach our goal of AI-assisted diagnosis and severity assessments based on real-world, user-generated data
- Maintain a steady stream of deep learning experiments, choosing which abstractions not to build and building the right ones at impressive speed
- Contribute to and iterate on novel un/semi/supervised learning algorithms
- Optimize the ML infrastructure on AWS as it scales up
- Communicate hypotheses, your test & learn approach, progress and results to technical and non-technical team members
We’re looking for individuals to join our team who are hungry for impact within health care and want to contribute to solutions with potential to improve millions of lives.
As our ideal candidate, you have:
- 5+ years of industry and/or research experience in machine and ideally deep learning-focused roles
- Good grasp of neural networks, linear algebra, probability/stats, and computer science fundamentals – so usually you’d have a MS/PhD in Data Science/Machine learning/Computer Vision/Computer Science but this is not a requirement for exceptional candidates
- Experience in shipping products which leverage AI
- Hands-on, pragmatic and thorough execution when designing loss functions, tuning hyperparameters or debugging back prop equations
- Strong Python skills
- Ability to communicate – both written and orally – and document technical information clearly and succinctly to both technical and non-technical teams
- Disciplined approach to testing and quality assurance
- Experience with setting up pipelines for real-world machine learning problems, and preparing and processing real datasets, training classifiers, train/test split, etc
- Computer vision background is a big plus
- Experience with image processing
- Experience with GANs
- Experience working on data pipelines at scale
- Software engineering background
- Experience developing software as a medical device
- Good judgement on avoiding premature optimization and local maxima
- Pragmatic attitude, focused on shipping instead of infinite research
- Experience customizing neural networks with Tensorflow
- Want to grow into a leadership role
Apply by sending your resume and motivational letter to email@example.com
We will invite applicants for interviews on a rolling basis until we have found the right people.
Please if available include a link to your portfolio/GitHub for us to see samples of your projects.