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- Tasks: Develop AI solutions using Python and collaborate on innovative projects.
- Company: Leading Software and AI Development company in London with a flat hierarchy.
- Benefits: Salary up to £85k, flexible remote work, and top-notch training.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Experience in Python and solid knowledge of AI/ML required.
- Other info: Sociable team with great office perks for onsite work.
The predicted salary is between 43200 - 72000 £ per year.
Senior AI Engineer (NLP / LLMs) – remote (UK based)
£70-100k depending on experience
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 employer: Digital Waffle
Contact Detail:
Digital Waffle Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups or webinars, and connect with fellow AI enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects and any AI/ML work you've done. This is your chance to demonstrate your innovative thinking and problem-solving abilities to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to AI and Python, and be ready to discuss your ideas and how they can contribute to the company's goals.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find and apply for roles that match your skills. Plus, it shows you're serious about joining our team and helps us keep track of your application.
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python programming skills and any experience with AI/ML frameworks like Tensorflow or Pytorch. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and Machine Learning, and explain why you’re excited about working with us. Remember, we love innovative thinkers, so feel free to share your ideas on how you can contribute.
Showcase Your Projects: If you've worked on any cool AI or ML projects, make sure to mention them! Whether it's a personal project or something from your studies, we want to see your hands-on experience and creativity in action.
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. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at Digital Waffle
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in an Agile environment, and think of specific projects where you've used it. This will show that you’re not just familiar with the language but can also apply it effectively.
✨Showcase Your AI/ML Knowledge
Prepare to talk about your understanding of AI and Machine Learning concepts. Familiarise yourself with frameworks like TensorFlow, PyTorch, or Scikit-learn, and be ready to discuss how you've used them in past projects. This will demonstrate your technical expertise and passion for the field.
✨Be an Innovative Thinker
Since the company values innovative ideas, think of a few suggestions or improvements you could bring to their projects. During the interview, don’t hesitate to voice these ideas and back them up with reasoning. This shows that you’re proactive and ready to contribute to the team.
✨Understand the Company Culture
Research the company’s culture and values. Since they have a flat hierarchy, be prepared to discuss how you work collaboratively in teams. Highlight any experiences where you’ve contributed to group discussions or decision-making processes, as this aligns with their working style.
