Job Title: Machine Learning (ML) Engineer
Location: Hybrid (with travel to Manchester and London)
Employment Type: Permanent
Salary: Up to £65,000 per annum plus equity
About the Company:
Our client is an innovative AI startup operating in the Insurtech sector, focusing on the smart contract parametric insurance landscape. Recently funded and on the path to rapid, scalable growth, they are looking for a talented ML Engineer to join their team and contribute to their journey.
Role Overview:
As an ML Engineer, you will play a critical role in developing and implementing machine learning models to drive the company's products and services. You will work closely with data engineers and other stakeholders to ensure the scalability and performance of the solutions. This is a hybrid role with some travel to Manchester and London to meet business requirements.
Key Responsibilities:
- Design, develop, and deploy machine learning models
- Collaborate with data engineers to manage and optimise data pipelines
- Implement data governance and data management best practices
- Work with AWS tools, including Glue and SageMaker, to build and scale ML solutions
- Ensure the scalability and performance of machine learning solutions
- Participate in code reviews and contribute to the improvement of the development processes
Key Skills and Qualifications:
- Proven experience in machine learning and data engineering
- Proficiency in Python
- Experience with AWS services, particularly Glue and SageMaker
- Strong understanding of data governance and data management principles
- Ability to work collaboratively in a team environment
- Excellent problem-solving skills and attention to detail
What We Offer:
- Competitive salary up to £65,000 per annum
- Equity in the business
- Hybrid working model with travel to Manchester and London
- Opportunity to work in a dynamic and growing startup environment
- Chance to make a significant impact in the Insurtech industry
Morgan McKinley is acting as an Employment Agency and references to pay rates are indicative.
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