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- Tasks: Lead the development of innovative AI solutions and mentor a team of engineers.
- Company: Join LGC, a global leader in life science tools with a mission for safer world.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare and food safety through cutting-edge AI technology.
- Qualifications: Experience in AI/ML development and strong leadership skills required.
- Other info: Inclusive culture that values passion, curiosity, and integrity.
The predicted salary is between 36000 - 60000 £ per year.
LGC is a leading, global life science tools company, providing mission-critical components and solutions into high-growth application areas across the human healthcare and applied market segments. Its high-quality product portfolio is comprised of mission-critical tools for genomics and for quality assurance applications. LGC's tools play a key role in customer workflows from discovery applications through to commercial manufacture and enable its customers to: bring new diagnostics and therapies to market; progress research and development; optimise food production; and continuously monitor and enhance the quality of food, the environment and consumer products.
This role can ideally be based out of any of our UK sites working on a hybrid basis. The AI Engineering Lead is a senior technical leadership position collaborating with the Head of Data & AI. This role combines deep technical expertise in artificial intelligence with strong delivery and people management capabilities. The successful candidate will be responsible for leading the hands-on development and deployment of AI solutions while establishing a team of AI engineers and coordinating with third-party delivery partners.
The role requires a strong technical practitioner who can architect, develop and deliver both Machine Learning and Generative AI solutions. They will be expected to lead by example, maintaining hands-on involvement in solution development while guiding and mentoring their team. The ideal candidate will have a proven track record of successfully delivering AI projects from feasibility through to production deployment.
Working closely with the Head of Data & AI, business team members and IT colleagues, the AI Engineering Lead will ensure that AI initiatives are delivered on time, to specification, and in alignment with LGC's strategic objectives, AI governance framework and Technical standards.
Key Responsibilities- Technical Ownership
- Lead the end-to-end development and deployment of AI solutions, including Machine Learning models, Generative AI applications and Agentic solutions.
- Architect robust, scalable AI systems that integrate effectively with existing enterprise infrastructure.
- Maintain hands-on involvement in coding, model development, and technical problem-solving.
- Establish and enforce technical standards, procedures, and coding guidelines for AI development.
- Conduct code reviews and ensure high-quality work across all AI projects.
- Know the latest with emerging AI technologies and evaluate their potential application within LGC.
- Develop AI delivery capabilities through a mix of internal resources and 3rd party providers.
- Drive the successful delivery of AI projects on time, within budget, and to specification.
- Develop and maintain project plans, tracking progress and managing risks and dependencies.
- Manage the transition of AI solutions from development through to production and operational support.
- Ensure all AI solutions align with LGC's AI governance framework, data privacy regulations, and ethical guidelines.
- Implement appropriate testing, validation, and documentation practices for AI models.
- Be a key member and provide strategic input into the LGC AI Tech Council to shape ongoing AI strategies and technical landscape.
- Bachelor's degree or equivalent experience in Computer Science, Data Science, Machine Learning, or a related field; Master's degree or equivalent experience preferred.
- Extensive hands-on experience developing and deploying AI/ML solutions in production environments.
- Demonstrated experience with Generative AI technologies, including Large Language Models (LLMs), prompt engineering, RAG architectures, and AI agents.
- Experience leading technical teams or managing third-party delivery partners.
- Ideally strong proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
- Experience with cloud-based AI platforms and services (AWS SageMaker, Azure ML, Snowflake intelligence or equivalent).
- Excellent problem-solving skills and ability to translate business requirements into technical solutions.
- Strong communication skills with the ability to explain complex technical concepts to non-technical collaborators.
AI Engineering Lead in Westminster employer: LGC Group
Contact Detail:
LGC Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineering Lead in Westminster
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and tech space. Attend meetups, webinars, or industry events where you can chat with folks from LGC or similar companies. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Machine Learning and Generative AI. This is your chance to demonstrate your hands-on experience and technical prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your past projects and how you’ve led teams or collaborated with third-party partners. Practice explaining complex concepts in simple terms – it’s key for roles like the AI Engineering Lead.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, get that application in and let’s get the ball rolling!
We think you need these skills to ace AI Engineering Lead in Westminster
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineering Lead role. Highlight your experience with AI/ML solutions and any leadership roles you've had. We want to see how your skills align with our mission at LGC!
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 makes you a great fit for our team. Don’t forget to mention your alignment with our core values!
Showcase Your Projects: If you've worked on relevant AI projects, make sure to showcase them in your application. We love seeing real-world examples of your work, especially those that demonstrate your hands-on experience and problem-solving skills.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s straightforward and ensures your application goes directly to us. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at LGC Group
✨Know Your AI Stuff
Make sure you brush up on the latest trends in AI, especially around Machine Learning and Generative AI. Be ready to discuss your hands-on experience with these technologies, as well as any projects you've led or contributed to. This will show that you're not just a manager but also a technical expert.
✨Showcase Your Leadership Skills
Prepare examples of how you've successfully led teams or managed third-party partners in previous roles. Highlight your ability to mentor others and drive projects to completion. LGC values strong leadership, so demonstrating your capability in this area will be crucial.
✨Align with LGC's Values
Familiarise yourself with LGC's core values: passion, curiosity, integrity, brilliance, and respect. Think of ways you can embody these values in your work and share specific examples during the interview. This will help you connect with the company's culture and show that you're a good fit.
✨Prepare for Technical Questions
Expect to face some technical questions related to AI architecture, coding standards, and problem-solving scenarios. Brush up on your Python skills and be ready to discuss frameworks like TensorFlow or PyTorch. Practising coding problems can also give you an edge in demonstrating your technical prowess.