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.
About the role
By combining software engineering and data analysis, machine learning engineers enable machines to learn without the need for further programming. The purpose of this role is threefold split across our AWS (Sagemaker) and SAS platforms:
1) To build a viable machine learning and AI platform in support of allow the business to adopt machine learning products.
2) Build viable machine learning data products and support wider business teams building machine learning data products, so that the business continues to build beyond project inception - ensuring development is targeted towards sustainable deployment and growth.
3) To build re-usable frameworks to leverage the technology stack to its best abilities (i.e. optimisations for Teradata specific functions within machine learning data products)
Scope of Role
Leadership:
- The role works directly with business stakeholders on machine learning products to ensure the development is targeted towards sustainable deployment and growth.
- The role also works directly across a wider engineering and data team to align delivery of machine learning products.
- The role provides thought leadership in analytical teams, processes and platforms (people, systems, process).
- The role has influence in a team of over one hundred data professionals in the use of machine learning across the business, deploying effective communication and relevant training.
Nature and Area of impact:
- The role has influence in a team of over one hundred data professionals in the use of machine learning across the business, deploying effective communication and relevant training.
- 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.
- Successful machine learning engineers will develop and grow the use of machine learning within the business in a profitable and sustainable way.
Budget/Financial:
- Successful machine learning engineers will develop and grow the use of machine learning within the business in a profitable and sustainable way.
- Project/Deployment Cost/Benefit – Machine Learning Engineers have the responsibility to ensure the areas in which they commit time have a clear and tangible ‘path to value’ and that the benefit is worth the investment of time, effort, cost and limited resource.
- Direct Spend – The role is responsible for ensuring platform spend is accounted for and in line with budget and expectations.
- Strategic Direction – The role has direct and strategic influence on the ML & AI roadmap which has the potential to divert spend from existing providers to more cost-effective alternatives.
Key Responsibilities.
- Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture.
- Use exceptional mathematical skills, to perform computations and work with the algorithms involved in this type of programming.
- Produce project outcomes and isolate the issues that need to be resolved, to make programmes more effective.
- Collaborate with data engineers to build data and model pipelines.
- Manage the infrastructure and data pipelines needed to bring code to production.
- Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
- Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production.
- Use data modelling and evaluation strategy to find patterns and predict unseen instances.
- Apply machine learning algorithms and libraries.
- Communicate and explain complex processes to people who are not programming experts.
- Liaise with stakeholders to analyse business problems, clarify requirements and define the scope of the resolution needed.
- Analyse large, complex datasets to extract insights and decide on the appropriate technique.
- Research and implement best practices to improve the existing machine learning infrastructure and leverage existing platforms.
- Provide support to engineers and product managers in implementing machine learning in the product.
- Liaise with Financial Services to ensure opportunities for alignment on machine learning systems and processes.
Required skills and experience
- Proven track record of delivering machine learning at scale.
- A portfolio of past experience (blogs, talks, contributions to Open Source, Kaggle etc)
- A portfolio of past experience (blogs, talks, contributions to Open Source, Kaggle etc)
- Exceptional mathematical skills, in order to perform computations and work with algorithms
- The ability to explain complex processes to people who aren't technical experts.
- Highly proficient in at least one programming framework with an ability to produce readable, well-structured reusable code.
- Able to demonstrate experience in data manipulation, cleaning and pre-processed data
- Has a good understanding of machine learning domain and workflow, informed from practical experience.
- Real life experience of working with data and understanding the trade-offs and challenges of machine learning development and deployment.
- Able to define problems, scope and plan projects. Is able to self-manage the delivery of their objectives as part of a team.
- Strong Python coding skills
- Knowledge of AWS infrastructure (containers, VPC, security)
- Competence with infrastructure as code (Terraform, Cloudformation and similar)
- Knowledge of code deployments through CI/CD processes (Jenkins).
- Experience of a command line language (such as, C++ and Java)
- Linux SysAdmin skills
- Messaging (including, Kafka, RabbitMQ, ZeroMQ)
- Distributed systems tools (such as, Etcd, zookeeper, consul)
Benefits
- Up to 14% bonus based on Company and Personal performance.
- £1000 of flexible benefits allowance.
- 30 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.
