At Airtime we are all about innovation, because this is how we stay on top. Every one of us has a hunger to succeed and will stop for nothing less than excellence. Crucially, our ethos is underpinned by a culture of teamwork and our shared humility because all that we achieve, we achieve together.
Empowering
We keep the experience fresh with an innovative, original approach, marked by continuous introduction of unique features and benefits. We are about fresh, adaptable and impactful change that sets new standards and differentiates from competitors.
Magnetic
Genuinely engaging and deeply trustworthy. We connect easily, making every experience with us naturally appealing and memorable. Even the way we transform data into engaging, personalised insights is fun and visually appealing.
Uplifting
Bright and optimistic, we offer a positive escape from the mundane. We bring joy to everyday life, transforming routine into moments of happiness and satisfaction. Feel good with every interaction.
The Opportunity
We're looking for an experienced AI /ML Tech Lead to join our growing team. In this role, you will spearhead the design and development of our internal systems, meeting the requirements of our innovative and ambitious AI roadmap.
In this role, you will have a leadership role in defining technical and delivery strategy of Airtime’s AI strategy, including product selection, and system architecture, design and implementation, working closely with Data Science, Software Engineering and Data Engineering Teams.
Key Responsibilities
Lead technical selection, design and implementation of Airtime’s AI / ML strategy
Design, build, and optimise NLP models for applications such as natural language search and analytics, chatbots, and sentiment analysis.
Develop and integrate personalisation algorithms for tailored product and service recommendations and predictive analytics, across all customer touch points.
Implement MLOps best-practice delivery and operational pipelines, ensuring scalable and efficient deployment in an innovative, cloud-first fintech environment.
Work with Data Scientists to manage structured and unstructured, multi-faceted data, to extract insights and develop operational models that tangibly improve customer experience.
Collaborate with data engineers, product teams, and software engineers to integrate ML solutions into proprietary leading-edge fintech applications.
Research and implement state-of-the-art deep learning, reinforcement learning, and transformer-based NLP models (e.g., BERT, GPT).
Monitor model performance and security, retrain models as necessary, and optimise for real-time and automated decision-making.
Support the democratisation of advanced analytics by embracing models that help drive the adoption of intuitive tools, dashboards, and APIs that enable non-technical teams to leverage AI-driven insights.
Advocate for explainable AI (XAI) and ensure transparency in ML models for regulatory compliance and business adoption.
Hire, mentor and support junior ML engineers, fostering engineering excellence, knowledge-sharing and best practices within the team.
Requirements
Strong background in Machine Learning, Deep Learning, and NLP
Experience with transformer models (BERT, GPT, LLaMA, etc.)
Proficiency in SQL, Python and ML libraries such as TensorFlow, PyTorch, Hugging Face, and Scikit-Learn
Expertise in personalisation techniques (recommendation systems, user segmentation, dynamic pricing)
Experience working with sensitive and business critical data, able to perform behavioural and transactional analysis, and work with propensity models
Hands-on experience deploying models in cloud environments (AWS & GCP)
Strong understanding of MLOps (model monitoring, CI/CD for ML, versioning and deployment), with experience in MLOps frameworks such as MLFlow, ZenML, Kubeflow, Vertex AI and Sagemaker
Experience mentoring and coaching junior engineers to enhance team capability
Experience with data visualisation and analytics tooling (e.g., Thoughtspot, Streamlit, Metabase, Tableau, Power BI, etc.) to make ML insights accessible across the business
Colleague Benefits
Share options.
23 days annual leave, plus one for each year served (capped at 28).
Birthday leave.
Learning & development budget / time allocation
Flexible start & finish hours 06:30 - 10:30 am
Life assurance at 5x salary
Health cash plan
Virtual GP appointments for you and your family
24/7 helpline for physical and mental health support, counselling, and other wellbeing resources
Private Medical Insurance
Hybrid working between home and office
City centre location with brand new fit out (when in the office)