Machine Learning Engineer
- Data Science
About the role
Machine Learning Engineer – Edinburgh (Fully Remote Working Options)
£50,000 - £60,000 + Package
MBN are partnering with a scale up FinTech known as being a pioneer of Open Banking. The company are looking to appoint a Machine Learning Engineer to join their award-winning business.
You’ll have the opportunity to work on their groundbreaking personal finance app leveraging the UK’s broadest transactional dataset to create, productionise and maintain machine learning models that understand and predict consumer spending habits.
Here’s what the company will offer you:
- The chance to collaborate and learn from a team of highly talented Data Science and Data Engineers who want to be positively challenged.
- The freedom and creativity to get the job done in the best way you see fit.
- Be accountable, celebrate your wins and look for ways to constantly improve yourself, your product and your work.
- Lead on a variety of machine learning projects with the autonomy to solve difficult problems and develop cutting edge solutions.
Here’s what a Machine Learning Engineer will look like here:
- You can inspire, collaborate and challenge working as part of a team but are equally comfortable working autonomously.
- You have a good understanding of the full model lifecycle having experience creating different types of machine learning models and have been involved in their production.
- You have strong programming skills preferably in Python, C, C++ or Rust.
- You have experience applying NLP techniques to business problems and are well-versed with different techniques and algorithms on structured and unstructured datasets. (Advantageous)
- You have experience in monitoring and improving services on AWS. (Advantageous)
- You like to keep yourself abreast with the latest research, techniques and algorithms within machine learning and are not afraid to apply techniques across different domains.
- You are passionate about productionising your prototypes and seeing them achieve full value.