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- Tasks: Lead the development of cutting-edge AI solutions and mentor a team of tech enthusiasts.
- Company: Join Kainos, a forward-thinking company at the forefront of AI innovation.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for continuous learning.
- Why this job: Make a real impact in AI while collaborating with talented professionals in a dynamic environment.
- Qualifications: Experience in deploying AI/ML solutions and strong Python skills are essential.
- Other info: Fast-paced culture with excellent growth opportunities and a focus on responsible AI practices.
The predicted salary is between 43200 - 72000 £ per year.
hackajob is collaborating with Kainos to connect them with exceptional tech professionals for this role. As a Lead AI Engineer at Kainos, you will deliver advanced AI solutions leveraging state-of-the-art machine learning, generative and agentic AI technologies. You will drive the adoption of modern AI frameworks, AIOps best practices and scalable cloud-native architectures. Your role will involve hands-on technical delivery, collaborating with customers to translate business challenges into trustworthy AI solutions and ensuring responsible AI practices throughout. As a technical mentor, you will foster a culture of innovation, continuous learning, and engineering excellence. It is a fast-paced environment, so it is important for you to make sound, reasoned decisions. You will do this whilst learning about new technologies and approaches, with talented colleagues that will help you to develop and grow. You will support your colleagues and more junior developers, providing direction support as you solve challenging problems together.
Minimum (essential) Requirements
- Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection).
- Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc).
- Experience developing solutions at scale on cloud platforms (Azure & AWS), containerisation and orchestration tools such as Kubernetes and Docker.
- Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data.
- Understanding of responsible AI principles, model interpretability, and ethical considerations.
- Strong interpersonal skills and team working.
Desirable
- Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost).
- Experience with data storage for AI, vector databases, semantic search, and knowledge graphs.
- Contributions to open-source AI projects or research publications.
- Familiarity with AI security, privacy, and compliance standards e.g. ISO42001.
Lead AI Engineer in Shrewsbury employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer in Shrewsbury
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field, attend meetups, and join online forums. The more people you know, the better your chances of landing that Lead AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving modern frameworks and cloud solutions. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex AI concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to connect with Kainos and other companies looking for top talent like you. Plus, it shows you're serious about the opportunity!
We think you need these skills to ace Lead AI Engineer in Shrewsbury
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with AI/ML solutions in your application. We want to see how you've deployed these technologies in real-world scenarios, so don’t hold back on the details!
Tailor Your Application: Take a moment to customise your application for the Lead AI Engineer role. Use keywords from the job description and relate your past experiences to the responsibilities listed. This helps us see how you fit right in!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to understand your journey and achievements in AI.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at hackajob
✨Know Your AI Stuff
Make sure you brush up on your knowledge of modern AI/ML solutions, especially around prompt engineering and model evaluation. Be ready to discuss specific projects where you've deployed these technologies, as this will show your hands-on experience and understanding of the field.
✨Show Off Your Python Skills
Since strong Python skills are essential for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges that involve software engineering best practices like CI/CD and testing.
✨Talk About Teamwork
As a Lead AI Engineer, you'll need to collaborate effectively with others. Think of examples where you've worked in a team to solve complex problems or mentored junior developers. Highlight your interpersonal skills and how you foster a culture of innovation.
✨Understand Responsible AI
Be prepared to discuss responsible AI principles and ethical considerations. Companies are increasingly focused on these aspects, so showing that you understand model interpretability and can apply these principles in your work will set you apart from other candidates.
