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- Tasks: Lead the development of innovative AI solutions and support engineering teams in adopting AI.
- Company: Join a forward-thinking company focused on integrating AI across various business functions.
- Benefits: Enjoy a hybrid work model, competitive salary, and performance bonuses.
- Why this job: Be at the forefront of AI technology, shaping impactful solutions while mentoring future talent.
- Qualifications: Experience with Generative AI, strong coding skills in TypeScript and Python, and MLOps knowledge required.
- Other info: Ideal for those passionate about combining software engineering with AI to create real-world 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.
Locations
Lead AI Engineer - GenAI and ML employer: middle
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 by working on personal or open-source projects that involve LLMs or classical ML techniques. 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 field, especially those who have experience in MLOps and cloud platforms like Azure or GCP. Attend meetups, webinars, or conferences to make connections that could lead to referrals or insider information about the role.
✨Tip Number 4
Prepare to discuss how you've successfully collaborated with cross-functional teams in previous roles. Highlight your communication skills and ability to bridge the gap between technical and non-technical stakeholders, as this is crucial for the Lead AI Engineer position.
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 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 in 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.
Proofread Your Application: Before submitting your application, take the time to proofread it for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which is crucial for a technical role like this.
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 or other AI solutions, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Coding Proficiency
Since the role requires writing high-quality code in TypeScript and Python, brush up on your coding skills. You might be asked to solve a coding problem during the interview, so practice common algorithms and data structures in both languages to showcase your proficiency.
✨Understand MLOps Practices
Familiarise yourself with MLOps practices, including model deployment and monitoring. Be ready to discuss your experience with CI/CD pipelines and how you've ensured the reliability and security of AI solutions in previous roles.
✨Prepare for Collaborative Scenarios
This position involves working closely with engineers, product owners, and security teams. Think of examples from your past experiences where you successfully collaborated with cross-functional teams, and be prepared to discuss how you communicate complex technical concepts to non-technical stakeholders.
