Machine Learning Engineer
Liverpool, England, United Kingdom
The Very Group
About us
We are The Very Group and we’re here to help families get more out of life. We know that our customers work hard for their families and have a lot to balance in their busy lives. That’s why we combine amazing brands and products with flexible payment options on Very.co.uk to help them say yes to the things they love. We’re just as passionate about helping our people get more out of life too; building careers with real growth, a sense of purpose, belonging and wellbeing.
Role Purpose
As an ML Engineer, you will be responsible for supporting machine learning projects from inception through to deployment. You will work with cross-functional teams to develop data pipelines and implement models in production. This role is ideal for those with foundational experience in machine learning, eager to grow and learn in a supportive environment.
About the role
Technical Contribution
- Assist in developing machine learning models by preparing data, conducting experiments, and contributing to model evaluation.
- Build and maintain data pipelines to support machine learning workflows.
- Collaborate with senior team members to ensure models are deployed and maintained effectively in production environments.
Collaboration
- Work closely with mid-level and senior engineers on model development and deployment tasks.
- Support data engineers and analysts in building robust data pipelines for machine learning.
Nature and Area of impact
- Machine Learning has a direct and indirect influence on the way we interact with customers, from customer campaign selection to product recommendation to credit decisioning – machine learning has a positive impact on how we interact with customers.
- Machine Learning has a direct and indirect influence on the way we interact with customers, from customer campaign selection to product recommendation to credit decisioning – machine learning has a positive impact on how we interact with customers.
- Successful machine learning models significantly improve business performance through increases in sales and return and/or reduction in risk.
- Through accurate, robust, ethical, secure, and sustainable machine learning deliveries we ensure that our business and customers are served and protected.
- Part of this role is to ensure the strategic roadmap of machine learning within the retail business is in line with Financial Services development.
Key Responsibilities.
- Prepare datasets and perform data pre-processing, including cleaning, transformation, and feature engineering.
- Implement basic machine learning models under the supervision of senior engineers.
- Support model deployment, testing, and maintenance in production environments.
- Contribute to the monitoring and troubleshooting of deployed machine learning systems.
- Document code, processes, and best practices to ensure knowledge sharing across the team.
Required skills and experience
- Foundational knowledge of machine learning techniques and concepts.
- Basic understanding of data structures, algorithms, and statistical methods.
- Experience with Python and machine learning libraries (e.g., Scikit-Learn, Pandas).
- Familiarity with SQL and database querying.
- Understanding of cloud-based environments, preferably AWS, for model development and deployment.
- A degree in Computer Science, Mathematics, Data Science, or related fields (or relevant experience). ·
- A strong willingness to learn and grow in the field of machine learning.
Benefits
- On Target bonus (Business and Personal performance) of 4%
- £250 of flexible benefits allowance.
- 27 days holiday + bank holidays + option to purchase 5 additional days
- 6% matched pension
- Hybrid working - 3 days per week from our Speke HQ.
- Brand discount up to 25%
- Ongoing training and development.
Hiring Process
What happens next?
Our talent acquisition team will be in touch if you’re successful so keep an eye on your emails! We’ll arrange a short call to learn more about you, as well as answer any questions you have. If it feels like we’re a good match, we’ll share your CV with the hiring manager to review. Our interview process is tailored to each role and can be in-person or held remotely.
You can expect a three-stage interview process for this position:
1st Stage - An initial informal chat with a member of our TA Team.
2nd stage - A 30-45 minute video call with a member of the hiring team to discuss your skills and relevant experience. This is a great opportunity to find out more about the role and to ask any questions you may have.
3rd Stage – A more formal interview which is split into behavioural and technical questions, this will be with a number of the team and is likely to last around 2 hours.
As an inclusive employer please do let us know if you require any reasonable adjustments.
Equal opportunities
We’re an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Computer Science Data pipelines Engineering Feature engineering Machine Learning Mathematics ML models Model deployment Pandas Pipelines Python Scikit-learn SQL Statistics Testing
Perks/benefits: Career development Equity / stock options Flex hours
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