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For Companies At a Glance
- Tasks: Design and deploy advanced AI solutions using NLP and LLMs for real-world applications.
- Company: High-growth SaaS company focused on impactful AI technology.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Why this job: Join a mission-driven team and make a difference with cutting-edge AI solutions.
- Qualifications: Experience in AI/Machine Learning, strong NLP and LLM expertise required.
- Other info: Dynamic role with mentorship opportunities and a focus on continuous improvement.
The predicted salary is between 60000 - 84000 £ per year.
A high-growth SaaS company is hiring a Senior AI Engineer to help build intelligent, mission-critical systems used in highly regulated environments. The platform applies machine learning and large language models across complex, end-to-end data workflows, solving real-world problems with measurable social impact.
The Role
As a Senior AI Engineer, you’ll design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning outcomes, balancing experimentation with real-world delivery.
What You’ll Be Doing
- Designing and developing NLP and LLM-driven solutions for complex, real-world use cases
- Fine-tuning and adapting foundation models using domain-specific data
- Building evaluation frameworks, prompt testing tools and data preprocessing pipelines
- Monitoring, optimising and maintaining deployed models for performance, cost and reliability
- Implementing explainability, fairness and bias-mitigation strategies
- Collaborating on MLOps pipelines, CI/CD workflows and production deployments
- Mentoring junior engineers and promoting best practices across the team
- Staying current with advances in AI, NLP and MLOps to drive continuous improvement
What We’re Looking For
- Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership
- Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents)
- Experience translating research and experimentation into production systems
- Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management
- Hands-on experience with Docker and Kubernetes
- Strong communication skills and experience mentoring or leading others
Nice to Have
- Experience working in regulated or sensitive domains
- Exposure to graph-based retrieval techniques
- Experience with Azure ML and DevOps integrations
Artificial Intelligence Engineer in Broughton employer: Digital Waffle
Contact Detail:
Digital Waffle Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Broughton
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning space, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your NLP and LLM projects. Whether it's GitHub repos or a personal website, let your work speak for itself. We love seeing what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts simply, as you'll need to collaborate with various teams. We want to see how you can communicate your ideas!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate individuals who are ready to make an impact in the AI world.
We think you need these skills to ace Artificial Intelligence Engineer in Broughton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with NLP and LLMs. We want to see how you've taken models from research to production, so don’t hold back on those details!
Showcase Your Projects: Include specific projects where you’ve designed and developed AI solutions. We love seeing real-world applications, so share the impact your work has had in previous roles.
Be Clear and Concise: When writing your cover letter, keep it straightforward. We appreciate clarity, so explain how your skills align with our needs without fluff. Let’s get to the point!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Don’t miss out!
How to prepare for a job interview at Digital Waffle
✨Know Your NLP and LLMs Inside Out
Make sure you brush up on your knowledge of natural language processing and large language models. Be ready to discuss specific techniques like transformers, fine-tuning, and retrieval-augmented generation (RAG). Prepare examples from your past work where you've successfully implemented these technologies.
✨Showcase Your End-to-End Model Ownership
Be prepared to talk about your experience with the entire model lifecycle. Highlight projects where you took models from research to production, detailing the challenges you faced and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Familiarise Yourself with MLOps Practices
Since this role involves collaboration on MLOps pipelines and CI/CD workflows, make sure you understand these concepts well. Discuss any tools you've used, like Docker and Kubernetes, and how you've applied them in your previous roles to optimise model performance and reliability.
✨Prepare for Behavioural Questions
Expect questions about teamwork and mentoring, as you'll be working closely with other engineers and possibly leading junior team members. Think of examples that showcase your communication skills and how you've promoted best practices in your previous teams.
