Please note: we are looking for candidates to be based in and around Lodnon and are happy to come to our London office 3-4 times per. week.
If you are based outside of London, you
must be happy to frequently travel to our office.
About Skin Analytics
Skin Analytics is an award-winning digital health company that has launched the world's first AI-supported Skin Cancer pathway for a faster skin cancer diagnosis. Our AI as a Medical Device (AIaMD) is deployed in 13 NHS organisations, and growing. We are leading the way in leveraging AI technology to address the demand and capacity crisis facing Dermatology safely.
We are a team of passionate people who want to build a future where no one dies from skin cancer.
The Role
Interested in building world-changing technologies, and deploying AI at the intersection of artificial intelligence and medical diagnostics? Skin Analytics is offering a role in our machine learning team to design and deploy AI models into healthcare pathways.
Skin Analytics is a multiple award-winning healthcare company building a clinical quality diagnostic service for skin cancer using artificial intelligence. We work with the NHS and private insurers to deliver better pathways for patients, leading to better patient outcomes and lower costs for healthcare systems.
The role will involve building innovative AI solutions, across a range of data modalities, with a focus on computer vision. We can provide the data, compute, support and infrastructure needed to help you build powerful AI diagnostic tools, and see them deployed safely and effectively into the real world.
The role will be office-based, in Farringdon, London.
Requirements
Responsibilities
- Working to build solutions to solve computer vision or machine learning problems, in a fast-paced, interdisciplinary environment
- Contribute to the design, implementation and validation of algorithms focused on image classification, generation, segmentation and localisation in the domain of medical imagery
- Working on research problems within a product development timeline
- Developing practical solutions to difficult problems
- Able to communicate effectively with the products and development teams to transfer technologies into our commercial pipeline
- Continuously develop and maintain knowledge of the latest machine learning techniques with a view to improving our machine learning algorithms
Required Experience
- Masters or Ph.D. in computer vision, image processing or machine learning related discipline
- Applying machine learning techniques to medical applications
- Designing machine learning models and neural network architectures, including convolutional neural networks and transformers
- Strong code development skills, preferably in Python, and machine learning
- Strong documentation skills.
- Highly motivated, with good verbal and written communication skills
Interview process
- 1st Stage: Screening Call with our Talent & People Lead (30 mins)
- 2nd Stage: Competency-based interview with Hiring Manager (45 mins)
- 3rd Stage: A take home assignment, followed by a discussion of the project Presentation and general culture interview (60 mins)
Skin Analytics manufactures medical devices and complies with ISO standards 13485 and 27001. As part of your employment, you will be assigned Quality Management System (QMS) and Information Security Management System (ISMS). We require that our employees agree to complete their assigned training and diligently follow all company quality management and information security processes.
Benefits
- Competitive salary
- Bonus Structure
- Share options package - all our employees have ownership in the company
- Private healthcare incl. Partner & children
- 25 days annual leave (trialling increase to 26 days plus a company shutdown in August)
- Enhanced parental leave - includes adoption & foster
- Training budget
- Besides weekly catch-ups, monthly meetings to talk about you, and your ambitions and make plans
- Lots of fun social activities including company offsite!
The Real Stuff
Skin Analytics embraces and is committed to diversity and equal opportunities. We are dedicated to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.
