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For Companies At a Glance
- 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: Shape the future of AI while collaborating with talented teams in a dynamic environment.
- Qualifications: Experience in Generative AI, ML techniques, and proficiency in TypeScript and Python required.
- Other info: Opportunity to work with cutting-edge technologies and make a real impact.
The predicted salary is between 48000 - 64000 £ 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.
Contact Detail:
middle Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer - GenAI and ML
✨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 help you engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your hands-on experience with LLMs and classical ML techniques by working on personal projects or contributing to open-source initiatives. Having tangible examples of your work can set you apart from other candidates and demonstrate your practical skills.
✨Tip Number 3
Network with professionals in the AI and ML fields. Attend meetups, webinars, or conferences to connect with others who share your interests. Building relationships can lead to referrals and insider information about job openings at companies like us.
✨Tip Number 4
Prepare to discuss MLOps practices and your experience with cloud platforms during interviews. Be ready to explain how you've deployed ML models in production environments and the challenges you've faced. This will show your depth of knowledge and readiness for the role.
We think you need these skills to ace Lead AI Engineer - GenAI and ML
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 skills and achievements relevant to the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with the responsibilities of the Lead AI Engineer position. Mention any relevant projects or experiences that showcase your ability to lead and mentor others in AI development.
Showcase Your Technical Skills: Include a section in your application that details your hands-on experience with MLOps practices, CI/CD pipelines, and cloud platforms like Azure or GCP. Highlight any specific tools or technologies you have used, such as Terraform or Ansible.
Demonstrate Collaboration Experience: Provide examples of how you have successfully collaborated with cross-functional teams, including engineers, product owners, and security teams. This will show your ability to communicate effectively with both technical and non-technical stakeholders.
How to prepare for a job interview at middle
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with Generative AI technologies and classical machine learning techniques. Highlight specific projects where you've successfully implemented LLMs, embeddings, or other relevant systems.
✨Demonstrate Coding Proficiency
Since the role requires proficiency in TypeScript and Python, be ready to showcase your coding skills. You might be asked to solve a problem on the spot, so practice writing clean, maintainable code before the interview.
✨Discuss MLOps Practices
Familiarise yourself with MLOps practices, CI/CD pipelines, and model deployment strategies. Be prepared to explain how you have applied these in previous roles, especially in cloud environments like Azure or GCP.
✨Prepare for Collaboration Questions
As this role involves working with various teams, think of examples that demonstrate your ability to communicate effectively with both technical and non-technical stakeholders. Highlight any mentoring experiences with junior engineers as well.
