The world isn't standing still, and neither is Allstate. We're moving quickly, looking across our businesses and brands and taking bold steps to better serve customers' evolving needs. That's why now is an exciting time to join our team. You'll have opportunities to take risks, challenge the status quo and shape the future for the greater good.
You'll do all this in an environment of excellence and the highest ethical standards - a place where values such as integrity, inclusive diversity and accountability are paramount. We empower every employee to lead, drive change and give back where they work and live. Our people are our greatest strength, and we work as one team in service of our customers and communities.
Allstate operate a very flexible hybrid working policy that will allow you to design your working week in collaboration with your manager with a blend of remote and office working for NI based employees as well as condensed working patterns (4 day week/9 day fortnight). Employees based in GB will be employed on a permanent remote working contract.
Join our team and you'll find challenge and reward in a culture of innovation, support and balance.
Belfast/ Derry-Londonderry/ Strabane/ Remote, GB
Your role in the team
The purpose of the Data & Intelligent Systems Fast Forward team is to research & incubate innovative solutions to solve Allstate's most challenging and interesting problems.
As a Lead Machine Learning Engineer, you will:
Work in a highly talented diverse team.
Lead the development of a variety of machine learning projects including computer vision, nlp and recommender systems,
Be encouraged to continuously learn new skills, technologies, and tools.
Identify areas for innovation and have the freedom to explore and test out your ideas in PoCs.
So, what are the essential criteria to apply?
All candidates must evidence an existing right to work in the UK'
Undergraduate degree in Computer Science/Mathematics/Physics or equivalent experience
3+ years' postgraduate experience in machine learning or PhD in a relevant area.
Strong programming background
Hands on experience developing machine learning models.
Track record of applying models to solve real world problems
We also have some desirable criteria
Track record of leading the end to end development of machine learning products
Tensorflow, PyTorch or Similar Deep Learning framework
Experience training transformer models
Experience with structured and unstructured data using Hadoop/RDMS/SQL
Knowledge of cloud platforms, cloud data lakes & cloud DB technologies
Experience with collaboration & deployment tools for coding such as GitHub, AWS, Jenkins, Azure, Docker
What we offer
As Digital DNA's Workplace of the Year 2020 & 2022 winners, we offer a generous benefits package that includes flexible annual leave entitlement, dental and healthcare insurance, an attractive pension package and discounts on gym memberships, public transport and parking.
Allstate invests heavily in your development, as an employee you will have access to multiple world-class learning platforms and courses from our award-winning in-house Learning & Development team.
We pride ourselves in providing clear career paths and opportunities for internal mobility allowing you to further develop within the organisation.
We encourage a better work life balance and you'll have the opportunity to apply for various flexible working arrangements.
Statement on Fair Employment and Equal Opportunities
Allstate NI wishes to ensure equal opportunity is given to all job applicants. This company will not discriminate on the grounds of race, gender (including gender reassignment status), sexual orientation, religious belief, political opinion, marital status, age or disability.
We are an equal opportunities employer. We welcome applications from all suitably qualified persons. However, as women are currently under-represented in our workforce, we would particularly welcome applications from women. All appointments will be made on merit.
Applicants should note Allstate NI complete AccessNI background checks on all candidates offered a position.
The closing date for receipt of applications is Tuesday 6th December 2022