We can offer you the chance to help make the UK a safer place through innovation, working in partnership with government and law enforcement organisations on some of the most challenging data and technology problems out there.
We strongly encourage candidates of all different backgrounds and identities to apply. We are committed to building an inclusive, safe and supportive environment that allows everyone to do their best work. We are happy to support any accessibility or neurodiversity requirements that you may need during the recruitment process.
We’ve been around for about eight-years and gone from being a little-known tech start-up to creating our very own community at the heart of the tech and digital epicentre of the UK - Manchester.
Our name Naimuri is Japanese and simply means…
‘nai’ meaning ‘not’
‘muri’ meaning ‘overburden’
These principles apply to every aspect of an organisation from technology, process and infrastructure, through to people, culture and leadership. This means that we empower our teams to do what they think is the right thing, giving them the skills and confidence to explore new ways of working, and to create a bias-free environment, where all our people feel comfortable collaborating to deliver the finest ideas and solutions in an agile environment.
Our business is focused on 4 cornerstones, which shape and underpin the way in which we go about work and treat each other. These are: Wellbeing, Empowerment, Perpetual Edge and Delivery.
People and culture are at the heart of Naimuri, so that collectively, we can realise our mission of ‘making the UK a safer place to be’.
About the role and team
Naimuri’s Data Science Capability is a fast-growing team with a diverse skillset, including mathematicians, computer scientists, data engineers, data platform engineers and machine learning (ML) engineers like yourself.
Our ML engineers are capable of:
Curating, labelling and sometimes synthesising data for ML training use
Performing ML experiments that involve loading and preparing data, and training and evaluating ML models, including deep neural networks, for tasks such as classification, localisation, regression, and generation
Productionising ML capabilities through software engineering, such as creating web applications for serving ML models, evaluating models for performance, calibration, and other criteria, and retraining to pass customer-derived quality gates
Working with MLOps engineers, data platform engineers and data engineers to build reproducible training pipelines, build deployment pipelines, and serve ML capabilities effectively
Working with AI assurance engineers to devise assurance workflow and identify requisite datasets, pre-inference transforms, and post-inference evaluation metrics
Working both on local devices and on the cloud.
Our more senior ML engineers are capable of:
Understanding the elements of neural networks, such as convolutional layers, attention mechanisms, and fully connected layers, and how and why they architected together;
Understanding which activation functions and loss functions to use in different ML use cases;
Designing and prototyping novel neural network architectures;
Working on different kinds of architecture for different data types and use cases, including Computer Vision, Natural Language Processing, Generation, Forecasting, and Trend Analysis.
You have a scientific approach to your work, above and beyond that which is inherent in the ML lifecycle itself. You have a keen interest in the rapidly growing field of machine learning, and are eager to try new techniques and architectures. You hold strong opinions on how to tackle challenges, but are also open to others’ ideas and can work within project constraints, such as user requirements, project deadlines, and budgets. You can work in a team alongside other experts performing tasks such as data analytics, MLOps, data engineering, and AI assurance. You have a desire to follow best practise and team ways of working, but will challenge those when appropriate and champion better technologies and ways of working when the opportunity arises.
You might have an educational background in Computer Science, or even Data Science or Machine Learning specifically, but you might have come from a more traditional mathematics or sciences background, such as Physics or Behavioural Science. Or maybe you’ve arrived at machine learning from leftfield and have a story to tell about how you got there. Passion, drive, and attitude will win us over more than anything else!
Pay and benefits
Naimuri pays competitively within the industry based on your role's base location rates. The salary for this position is dependent upon your experience and is relative to our current people. It is vital to us that all our people are paid commensurate, to ensure everyone feels valued. We assess seniority relative to the team at Naimuri during the interviewing process.
A full time working week is 37.5 hours and you have flexibility over when you give that time. We also offer part-time working which can be discussed during the recruitment process.
Our core hours are 10:00am - 3:00pm and our office hours are between 7:30 and 18:00 Monday to Friday.
Flexible/Hybrid working options
A performance bonus
Pension matched 1.5x up to 10.5%
AXA group 1 medical cover
Personal training budget
Holiday buy-back scheme
We want to ensure that you feel comfortable and confident when interviewing with us. To help you prepare, our recruitment team will discuss the process in more detail with you when you apply.
We are happy to support any accessibility or neurodiversity requirements.
If you would like to apply for this position please send your latest CV to email@example.com
We look forward to hearing from you !