AI Engineer

JR United Kingdom; Norwich; On-site; GBP 55,000 - 80,000; Full time

Job summary

A leading company in AI and analytics is seeking an AI Engineer to join their Data and AI team. The successful candidate will be responsible for designing and deploying AI/ML solutions that drive client engagement in Financial Services, leveraging their expertise to innovate and provide actionable insights.

Qualifications

• 4+ years in AI/ML model development.
• Strong proficiency in Python and SQL.
• Experience in deploying AI solutions for business.

Responsibilities

• Lead AI/ML initiatives from design to production.
• Develop predictive models for marketing insights.
• Ensure model performance and governance compliance.

Skills

Python

SQL

Machine Learning

Data Analysis

Problem Solving

Education

Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Applied Mathematics

Tools

Scikit-learn

TensorFlow

PyTorch

Docker

Airflow

Job description

Social network you want to login/join with:

Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the unlimited opportunities digital offers. Our reputation is built on a comprehensive suite of engineering services, a dedication to solving clients’ toughest technology problems, and a commitment to continuous improvement.

Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon now has a global presence.

About the Role

We are seeking a highly motivated and experienced AI Engineer to join our Data and AI team. This role is ideal for someone who has a strong track record of designing, developing, and deploying AI/ML solutions in a business context—from ideation through to production.

You will play a pivotal role in shaping and implementing advanced AI-driven insights and personalization strategies that optimize client engagement and campaign performance across digital, CRM, and relationship management channels for our Financial Services client.

Key Responsibilities

• End-to-End AI Solution Delivery: Lead AI/ML initiatives from conceptual design to production deployment, including problem scoping, data acquisition, model development, validation, deployment, and monitoring.
• AI-Driven Marketing Insights: Develop predictive and generative models to support audience segmentation, personalization, channel optimization, lead scoring, and campaign measurement.
• Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions.
• Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance.
• Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new ideas, frameworks, and techniques that can be applied to marketing use cases.
• Data Strategy: Collaborate with data engineering teams to ensure the availability of clean, structured, and enriched data pipelines required for model training and inference.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, or a related field.
• 4+ years of experience in building and deploying AI/ML models in a business setting, ideally in a regulated or enterprise environment.
• Demonstrated experience taking AI solutions from ideation to production—successfully navigating cross-functional stakeholders, data challenges, and deployment hurdles.
• Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders.
• Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker.
• Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention.
• Experience working with multi-channel marketing data: CRM (e.g., Salesforce), email, web analytics, social media, and paid media.
• Excellent problem-solving skills, business acumen, and the ability to translate complex models into actionable insights for non-technical stakeholders.

Tools/Frameworks:

• PyCaret, Prophet, or custom implementations for time series
• A/B testing frameworks (e.g., DoWhy, causalml)

Programming & Data Tools :

• Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc.
• SQL: Advanced querying for large-scale datasets.
• Jupyter, Databricks, or notebooks-based workflows for experimentation.

Data Access & Engineering Collaboration :

• Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery)
• Familiarity with data pipelines and orchestration tools like Airflow
• Work closely with Data Engineers to ensure model-ready data and scalable pipelines.

Nice to have

• Prior experience working in financial services or within a marketing analytics function.
• Knowledge of customer lifetime value modelling, recommendation systems, or NLP-based content personalization.
• Exposure to regulatory considerations in marketing data usage (e.g., GDPR, data privacy in finance).