Senior Machine Learning Engineer

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)

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.
• 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.

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)
• 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:

1. An initial informal chat with a member of our TA Team.
2. A 30-45 minute video call with a member of the hiring team to discuss your skills and relevant experience.
3. 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.