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For Companies At a Glance
- Tasks: Design and develop cutting-edge NLP and LLM solutions for real-world applications.
- Company: High-growth SaaS company focused on impactful AI systems.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Why this job: Join a mission-driven team and make a difference with advanced AI technology.
- 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 Livingston employer: Digital Waffle
Contact Detail:
Digital Waffle Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Livingston
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and tech space. Attend meetups, webinars, or even online forums where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NLP and LLMs. Share your GitHub or any relevant work on platforms like LinkedIn. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to AI and MLOps. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the role.
We think you need these skills to ace Artificial Intelligence Engineer in Livingston
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior AI Engineer. Highlight your experience with NLP and LLMs, and don’t forget to showcase any hands-on projects that demonstrate your skills in building and deploying models.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background aligns with our mission at StudySmarter. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex problems using AI. We love seeing candidates who can balance experimentation with real-world delivery, so share any relevant experiences that highlight this ability.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to showcase your skills directly to our team!
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, from research to production. Highlight any projects where you took ownership of a model, 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 with MLOps teams, it’s crucial to understand CI/CD workflows and model monitoring. Brush up on tools like Docker and Kubernetes, and be ready to discuss how you've used them in 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 others and guiding junior engineers. Think of examples that showcase your communication skills and ability to promote best practices. This will help you stand out as a collaborative team player.
