Artificial Intelligence and Machine Learning Engineer

We are on a mission to stop fraud and improve customer authentication. Fraud is a huge problem affecting millions of people, costing the UK nearly £7bn and representing 40% of all crime. We are changing this by providing organisations with real-time insight into the risk of a caller. We combine patented machine learning technology with our deep domain knowledge to prevent contact centre fraud and streamline customer experience.

You will be part of a cross-functional team, working across a variety of tasks from data science research and model development through to platform implementation and maintenance. You will use your knowledge of machine learning algorithms, frameworks, and methodologies to research and develop models for our cloud-based authentication and fraud systems, continuously iterating and evaluating model performance using appropriate metrics.

Explore and visualise data to discover innovative features and potential data sources. Engineer datasets, develop data pipelines, perform feature engineering, and write code to train, deploy, monitor, and run real-time inferences. Build and monitor ML models, addressing issues such as overfitting, underfitting, data leakage, and drift. You will use your expertise in engineering and DevOps/MLOps to manage our machine learning platforms using AWS SageMaker and other AWS services.

Design, build, and improve scalable public cloud-based machine learning platforms. Develop robust data pipelines and workflows, contributing to platform reliability, scalability, and observability through effective monitoring, alerting, and performance tuning.

Some of the technologies currently used by the Intelligence Group include:

• ML Platform: Amazon SageMaker (Sagemaker Studio IDE, Sagemaker Training / Processing / Pipeline / Endpoints, Feature Store, Model Registry, Model Monitor)
• Data Processing: Amazon Athena, Apache Iceberg, AWS Glue, Spark
• ML Frameworks: Scikit-Learn, Hugging Face
• ML Algorithms: Tree-based (XGBoost), Deep Learning
• Programming and Development Tools: Python
• Data Processing Libraries, e.g. SQL

Smartnumbers values diversity of experience. We expect that you will have around 2 to 3 years’ commercial experience across a range of platform engineering and data science responsibilities. You should be able to own tasks end-to-end, take responsibility for the quality of deliverables, and drive ML and MLOps best practices and tooling to consistently enhance our models and ML platform.

Understanding of machine learning fundamentals: data analysis, feature engineering, algorithms, performance metrics etc. Understanding of software engineering fundamentals: clean code, source control, SOLID principles, design patterns, refactoring etc. Understanding of DevOps/MLOps practices: Infrastructure as Code, data pipelines, CI/CD, containerisation, orchestration/pipelines, system & model monitoring.

Comfortable digging deep into either datasets or system logs to understand root causes or improve system performance. Proficient in Python, SQL, and data/ML frameworks like Pandas, Scikit-Learn etc. Experience with ML techniques and strategies, such as classical ML, deep learning, clustering, ensembling etc. Experience with MLOps techniques and building and maintaining scalable data pipelines and ML platforms. Experience with cloud services (preferably AWS) and infrastructure as Code.

As well as a competitive salary of circa £55k per annum, we also offer a comprehensive benefits package, covering a variety of areas, both professional and personal:

• Hybrid working style, with the expectation of two days in the office
• Family friendly benefits including paid parental leave policies
• An extensive health insurance policy for you, with an option to add your family members
• A workplace pension with Hargreaves Lansdown
• Life insurance of 4 x your salary
• A discretionary annual bonus of up to 10% of your salary
• Weekly self-development time to spend exploring your professional development interests
• 25 days of annual leave (plus bank holidays), your birthday off, and an opportunity to buy up to 5 days annual leave per year
• A holistic wellbeing support plan encompassing a variety of offerings to assist you
• Monthly £50 allowance to fund activities to best support your wellbeing
• Workshops and training to provide tools and guidance
• Employee assistance programme available to advise on personal, family or financial matters
• Fun social events during the year

You will receive equal treatment regardless of age, disability, neurodiversity, gender, gender identity, gender reassignment, marital or civil partner status, pregnancy or maternity, race, colour, nationality, ethnic or national origin, religion or belief, sex and sexual orientation.

We help companies in the fight against fraud. Our solutions help protect organisations from downstream fraud by ensuring the contact centre stays secure. Through our consortium of customers and partners, we enable organisations to work together to fight fraud by sharing intelligence and best practice.

Our cloud-based AI-powered platform uses direct access to the carrier network, shared data on known fraudsters from our consortium and machine learning technology to protect your contact centre and your customers.