Full job description

Lead AI/ML Engineer

As a Lead AI/ML Engineer in the leisure, travel & tourism industry, you'll focus on building and deploying machine learning models to drive analytics and decision-making. You'll play a vital role in shaping data-driven strategies that contribute to the organisation's success.

Client Details

Lead AI/ML Engineer

Our client is a leading UK organisation undergoing an ambitious data and AI transformation. Operating across multiple locations, they are investing heavily in modern analytics, machine learning and predictive modelling capabilities to support smarter decision-making and long-term business growth.

Description

Lead AI/ML Engineer

Engage with business stakeholders to understand operational and commercial challenges and translate them into AI and predictive analytics solutions.
Design, build and deploy machine learning models focused on forecasting, prediction and optimisation.
Develop solutions around areas such as demand forecasting, pricing, revenue, capacity and operational planning.
Work with data held within Databricks and Azure-based environments.
Build and maintain model training, evaluation and monitoring processes.
Advise on appropriate AI and machine learning approaches for business use cases.
Partner with data, engineering and technology teams to ensure solutions are production-ready and deliver measurable value.
Present insights and recommendations to both technical and non-technical stakeholders.
Contribute to AI best practice, governance and solution design discussions.

Profile

Lead AI/ML Engineer

A successful Lead AI/ML Engineer should have:

Strong experience in Data Science, Machine Learning or Predictive Analytics.
Proven expertise in forecasting and predictive modelling.
Advanced Python skills and experience with common ML libraries.
Strong SQL skills.
Experience working with Databricks and/or Spark environments.
Ability to translate business requirements into practical AI and ML solutions.
Experience communicating technical concepts to business stakeholders.
Strong problem-solving skills with a consultative mindset.
Comfortable working independently whilst collaborating across multiple teams.

Desirable

Experience delivering forecasting, predictive analytics or machine learning solutions in a data-rich commercial environment.
Experience supporting operational, financial, customer or commercial decision-making through data and AI.
Exposure to MLOps, MLflow or model lifecycle management.
Experience with Microsoft Azure, Fabric or AI technologies.

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Responsibilities

Full job description

Lead AI/ML Engineer

Client Details

Lead AI/ML Engineer

Description

Lead AI/ML Engineer

Engage with business stakeholders to understand operational and commercial challenges and translate them into AI and predictive analytics solutions.
Design, build and deploy machine learning models focused on forecasting, prediction and optimisation.
Develop solutions around areas such as demand forecasting, pricing, revenue, capacity and operational planning.
Work with data held within Databricks and Azure-based environments.
Build and maintain model training, evaluation and monitoring processes.
Advise on appropriate AI and machine learning approaches for business use cases.
Partner with data, engineering and technology teams to ensure solutions are production-ready and deliver measurable value.
Present insights and recommendations to both technical and non-technical stakeholders.
Contribute to AI best practice, governance and solution design discussions.

Profile

Lead AI/ML Engineer

A successful Lead AI/ML Engineer should have:

Strong experience in Data Science, Machine Learning or Predictive Analytics.
Proven expertise in forecasting and predictive modelling.
Advanced Python skills and experience with common ML libraries.
Strong SQL skills.
Experience working with Databricks and/or Spark environments.
Ability to translate business requirements into practical AI and ML solutions.
Experience communicating technical concepts to business stakeholders.
Strong problem-solving skills with a consultative mindset.
Comfortable working independently whilst collaborating across multiple teams.

Desirable

Experience delivering forecasting, predictive analytics or machine learning solutions in a data-rich commercial environment.
Experience supporting operational, financial, customer or commercial decision-making through data and AI.
Exposure to MLOps, MLflow or model lifecycle management.
Experience with Microsoft Azure, Fabric or AI technologies.