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- Tasks: Lead the development of innovative AI solutions and mentor junior engineers.
- Company: Join a forward-thinking company at the forefront of AI technology.
- Benefits: Enjoy a hybrid work model, competitive salary, and performance bonuses.
- Why this job: Make a real impact by shaping AI strategies and tools in a collaborative environment.
- Qualifications: Experience with Generative AI, strong coding skills in TypeScript and Python required.
- Other info: Opportunity to work with cutting-edge technologies and cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for a Lead AI Engineer to define and deliver the next phase of AI for our client. This role combines deep expertise in GenAI with strong hands-on experience in classical machine learning. You will play a key role in building internal AI tools, integrating scalable ML systems, and shaping how AI is used across the business.
Responsibilities
- Lead the development of GenAI solutions including LLMs, embeddings, and retrieval-based systems
- Design, build, and support internal platforms that help engineering teams adopt AI effectively
- Guide the adoption of classical machine learning models that address practical business problems
- Write high-quality, maintainable code in TypeScript and Python
- Drive excellence in MLOps practices including model deployment, monitoring, and governance
- Collaborate with engineers, product owners, and security teams to ensure solutions are secure and reliable
- Coach and mentor junior engineers and contribute to the overall strategy of the AI platform
What You Will Need
- Hands-on experience with Generative AI technologies such as LLMs, prompt engineering, and vector-based search
- Strong foundation in traditional ML techniques such as regression, classification, and clustering
- Proficiency in both TypeScript and Python for building robust applications and tools
- Knowledge of MLOps practices, CI/CD pipelines, and software delivery best practices
- Experience deploying ML models into production environments using cloud platforms such as Azure or GCP
- Ability to work in agile teams and communicate effectively with technical and non-technical stakeholders
Bonuses
- Experience with tools such as Terraform, Ansible, Packer, or ML platforms like Vertex AI and Azure ML
- Familiarity with cloud AI services such as Azure Vision or Google Vision AI
- Understanding of modern application architecture, including API-first design and service-oriented patterns
- Background in AI safety, model evaluation, or secure model deployment
This role is for someone who can combine strong software engineering skills with deep AI knowledge to build products that drive impact. If that sounds like you, we would love to hear from you.
Lead AI Engineer GenAI and ML in Basingstoke employer: Middle Recruitment Limited
Contact Detail:
Middle Recruitment Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer GenAI and ML in Basingstoke
✨Tip Number 1
Familiarise yourself with the latest trends in Generative AI and machine learning. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the AI and ML space, especially those who work in similar roles. Attend meetups, webinars, or conferences where you can connect with potential colleagues or mentors. Building these relationships can lead to valuable insights and even job referrals.
✨Tip Number 3
Prepare to discuss your hands-on experience with both Generative AI technologies and classical machine learning techniques. Be ready to share specific examples of projects you've worked on, particularly those that involved deploying models into production environments. This will showcase your practical skills and problem-solving abilities.
✨Tip Number 4
Demonstrate your understanding of MLOps practices by discussing how you would approach model deployment and monitoring. Familiarise yourself with tools like Azure or GCP, and be prepared to explain how you would ensure the reliability and security of AI solutions in a business context.
We think you need these skills to ace Lead AI Engineer GenAI and ML in Basingstoke
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Generative AI technologies, classical machine learning techniques, and proficiency in TypeScript and Python. Use specific examples to demonstrate your hands-on experience and achievements in these areas.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your skills align with the responsibilities of the Lead AI Engineer role. Mention your experience with MLOps practices and your ability to mentor junior engineers, as these are key aspects of the position.
Showcase Relevant Projects: If you have worked on projects involving LLMs, prompt engineering, or deploying ML models in production, be sure to include these in your application. Highlight your role in these projects and the impact they had on the business.
Prepare for Technical Questions: Anticipate technical questions related to AI, machine learning, and software development during the interview process. Brush up on your knowledge of CI/CD pipelines, cloud platforms like Azure or GCP, and modern application architecture to impress the interviewers.
How to prepare for a job interview at Middle Recruitment Limited
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with Generative AI technologies and classical machine learning. Highlight specific projects where you've implemented LLMs or other relevant systems, and be ready to explain the technical challenges you faced and how you overcame them.
✨Demonstrate Your Coding Skills
Since proficiency in TypeScript and Python is crucial for this role, consider bringing a portfolio of your code samples or discussing past projects. Be ready to solve coding problems on the spot, as this will showcase your ability to write high-quality, maintainable code.
✨Understand MLOps Practices
Familiarise yourself with MLOps practices, CI/CD pipelines, and model deployment strategies. Be prepared to discuss how you've applied these practices in previous roles, particularly in deploying ML models into production environments using cloud platforms like Azure or GCP.
✨Communicate Effectively
This role requires collaboration with various teams, so practice articulating complex technical concepts in a way that non-technical stakeholders can understand. Prepare examples of how you've successfully communicated with different teams in the past, ensuring everyone is aligned on project goals.
