At a Glance
- Tasks: Design and deploy innovative AI/ML solutions that enhance customer experiences.
- Company: Forge Holiday Group, a leader in creating memorable holiday experiences.
- Benefits: Up to £80,000 salary, 33 days holiday, and a performance bonus.
- Other info: Join a diverse team committed to ethical AI and personal growth.
- Why this job: Shape the future of AI while collaborating with talented teams.
- Qualifications: Strong experience in AI/ML, data pipelines, and collaboration skills.
The predicted salary is between 80000 - 80000 £ per year.
At Forge Holiday Group, we don’t just do holidays, we create memories. With market-leading brands like Sykes Holiday Cottages, Forest Holidays, and Bachcare in New Zealand, we’re 1,700+ strong and powered by four values: One Business One Team, Keep it Simple, Grow & Learn, Sustainable Impact.
Why This Role Stands Out:
- Innovation: Work hands-on with cutting-edge AI/ML tools and techniques to deliver real business impact
- Leadership: Mentor and collaborate with talented engineers, data scientists, and product teams
- Culture: People-first, values-driven, creativity & integrity at the core
- Impact: Shape AI-driven solutions that directly improve customer experience and business decisions
About the Role:
As a Senior AI/ML Engineer, you’ll play a pivotal role in designing, building, and deploying scalable AI and machine learning solutions across Forge Holiday Group. From data pipelines to machine learning models, your work will power customer interactions, internal insights, and commercial decision-making.
You’ll Own:
- Build and maintain end-to-end AI/ML pipelines in Microsoft Fabric
- Design, train, deploy, and monitor machine learning and deep learning models
- Implement MLOps best practices: versioned data & features, CI/CD pipelines, model promotion, and rollback
- Collaborate with data scientists, analytics engineers, product managers, and developers to turn business problems into AI solutions
- Uphold data quality, governance, security, and responsible AI practices
- Evaluate and adopt new tools and technologies to enhance our AI/ML platform
- Mentor junior colleagues and foster a culture of innovation and knowledge sharing
What You Need To Know:
- Salary: Up to £80,000 per annum
- Team: Work with cross-functional teams and mentor junior engineers
- Tools: Microsoft Fabric, Azure ML, MLflow, Spark, Python, SQL, CI/CD, and ML frameworks like TensorFlow, PyTorch, Scikit-learn
- Scope: End-to-end AI/ML solutions for multi-product, multi-region strategy
- Report To: Head of Data Science / CTO
- Location: Chester HQ, Hybrid working
- Working Pattern: 37.5 hours, Monday to Friday, 9am to 5:30pm
What We’re Looking For:
Essential:
- Strong experience designing, building and maintaining scalable data pipelines and architectures for AI/ML
- Familiarity with Microsoft Fabric (Data Engineering, Data Science, Real-Time Analytics) and Azure ML, including MLflow
- Proficiency with tools such as Apache Spark, Azure Data Factory, GIT, Python and SQL
- Skilled in developing, training and deploying machine learning models with frameworks like TensorFlow, PyTorch or Scikit-learn
- Strong understanding of data modelling, data governance, security and responsible AI practices
- Excellent problem-solving skills and the ability to explain technical concepts to varied audiences
- Ability to manage priorities and deliver results in a fast-paced environment
Desirable:
- Experience with generative AI, large language models (e.g. LangChain, vector databases) and retrieval-augmented generation
- Knowledge of AutoML, hyperparameter tuning and advanced MLflow features
- Experience with streaming and real-time data platforms
- Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker)
- Commercial awareness in e-commerce, travel or holiday-lettings sectors
- Experience mentoring others or leading technical workstreams
About You:
- Curious, innovative and passionate about data and AI
- A team player who values collaboration and honest communication
- Able to take ownership, work independently and deliver on commitments
- Supportive and approachable, with a willingness to share knowledge
- Committed to building ethical AI solutions that respect privacy, security and sustainability
Forge Holiday Group Benefits:
- Annual STIP Company-wide Bonus Scheme offering up to an additional 10% of your salary through our performance-based bonus program
- 33 days’ holiday (including bank holidays), plus up to 5 extra with long service. Option to purchase extra holiday days if you wish.
- A day off for your birthday
- 2 volunteering days per year.
- Enhanced parental leave (24 weeks maternity, 3 weeks paternity at full pay).
- Pension scheme with employer contributions
- Discounted and last-minute stays at Forest Holidays and Sykes Cottages for you, your friends & family.
- Special offers and discounts designed to enhance your overall wellbeing.
- Health cash plan & life assurance.
- Training & development opportunities.
- 24/7 mental health support.
- On-site gym and parking at Chester HQ (near train station).
- Employee savings scheme
- Long service awards and company events
We’re committed to diversity and inclusion and encourage you to bring your authentic self. Need adjustments for recruitment? Just ask.
AI / ML Engineer in Chester employer: Regional Marketing - Team
Forge Holiday Group is an exceptional employer, offering a dynamic work environment at our Chester HQ where collaboration and innovation thrive. With a strong focus on employee development, we provide ample growth opportunities through coaching and partnerships across various departments, ensuring that every team member can shape meaningful outcomes in their HR career. Our commitment to a supportive culture and the chance to make a real impact in the travel industry makes us a rewarding place to work.
StudySmarter Expert Advice🤫
We think this is how you could land AI / ML Engineer in Chester
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We think you need these skills to ace AI / ML Engineer in Chester
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Regional Marketing - Team.
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How to prepare for a job interview at Regional Marketing - Team
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Regional Marketing - Team uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
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While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
