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- Tasks: Design and deploy AI solutions that tackle real-world challenges in life sciences.
- Company: Fast-growing life sciences tech company focused on innovative AI applications.
- Benefits: Hybrid working model, career growth, health insurance, and access to cutting-edge AI tools.
- Why this job: Make a tangible impact in healthcare while working with advanced AI technologies.
- Qualifications: 3+ years in AI, strong Python skills, and experience with LLM APIs.
- Other info: Collaborative culture with opportunities for professional development and innovation.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for AI engineers who want to build production-ready AI solutions that tackle real-world challenges in life sciences, from RAG chatbots to agentic AI systems supporting evidence-driven projects. You will design, develop, and deploy AI systems that have measurable impact, influence patient access to treatments, and support decision-making in healthcare.
Our client is a fast-growing life sciences technology company with offices in the UK and Europe. They specialise in applying AI to accelerate patient access to treatments through practical, evidence-driven solutions. The company values collaboration, innovation, and creating a culture where employees can grow and make a tangible impact in healthcare.
Key responsibilities- Design, develop, and deploy AI systems with a focus on RAG chatbots and agentic AI.
- Lead real-world evidence projects, ensuring AI solutions are reliable, measurable, and impactful.
- Implement data pipelines, retraining workflows, and monitoring to maintain model performance.
- Design evaluation metrics to assess accuracy, latency, UX quality, safety, and real-world utility.
- Collaborate with product, software, and platform teams to deliver scalable, production-ready AI solutions.
- Champion software engineering best practices, including code reviews, testing, CI/CD, and reproducibility.
- Ensure AI solutions meet security, compliance, and responsible AI standards.
- Mid-to-senior AI engineer with 3+ years in data science or software engineering, including substantial AI experience.
- Strong Python skills and experience with LLM APIs (OpenAI, Anthropic, or similar).
- Expertise in GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face Transformers).
- Hands-on experience with RAG pipelines, vector databases (Pinecone, FAISS, Weaviate), and chatbot deployment.
- Proven experience with agentic AI (tool use, planning, multi-step reasoning) and production-level systems.
- Experience delivering AI solutions in real-world or evidence-driven projects, preferably in life sciences.
- Strong communication skills and understanding of AI ethics, bias mitigation, and responsible AI practices.
- Model fine-tuning, knowledge graphs, or multi-modal AI systems.
- AWS or other cloud platform experience for scalable GenAI deployment.
- Client-facing experience in AI projects.
- Hybrid working model (UK & Europe).
- Career development and professional growth opportunities.
- Collaborative culture with a focus on impact and innovation.
- Health insurance and wellness programmes.
- Access to cutting-edge AI tools and projects.
Artificial Intelligence Engineer in Slough employer: Aspire Life Sciences Search
Contact Detail:
Aspire Life Sciences Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Slough
✨Network Like a Pro
Get out there and connect with people in the AI and life sciences space! Attend meetups, webinars, or industry conferences. You never know who might be looking for someone just like you!
✨Show Off Your Skills
Create a portfolio showcasing your AI projects, especially those related to healthcare. Share your GitHub or any relevant work on platforms like LinkedIn. Let your work speak for itself!
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and understanding of AI frameworks. Practice common interview questions and be ready to discuss your past projects in detail.
✨Apply Through Our Website
Don’t forget to check out our website for job openings! Applying directly through us can give you an edge, as we’re always on the lookout for passionate candidates ready to make an impact in healthcare.
We think you need these skills to ace Artificial Intelligence Engineer in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with RAG chatbots, agentic AI, and any relevant projects in life sciences. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and how you can contribute to real-world challenges in healthcare. Let us know why you're excited about joining our team at StudySmarter.
Showcase Your Projects: Include links or descriptions of your previous AI projects, especially those that had a measurable impact. We love seeing practical examples of your work, so don’t hold back on showcasing your achievements!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our innovative team!
How to prepare for a job interview at Aspire Life Sciences Search
✨Know Your AI Stuff
Make sure you brush up on your AI knowledge, especially around RAG chatbots and agentic AI systems. Be ready to discuss your hands-on experience with LLM APIs and GenAI frameworks like LangChain or Hugging Face Transformers. The more specific examples you can provide, the better!
✨Showcase Real-World Impact
Prepare to talk about how your previous projects have made a measurable impact, particularly in life sciences. Highlight any evidence-driven projects you've worked on and how your AI solutions influenced patient access to treatments or improved decision-making in healthcare.
✨Collaboration is Key
Since the company values collaboration, be ready to discuss how you've worked with cross-functional teams in the past. Share examples of how you’ve collaborated with product, software, and platform teams to deliver scalable AI solutions. This will show that you’re a team player who can thrive in their culture.
✨Emphasise Best Practices
Familiarise yourself with software engineering best practices like code reviews, testing, and CI/CD. Be prepared to explain how you ensure your AI solutions meet security, compliance, and responsible AI standards. This will demonstrate your commitment to quality and ethical AI development.
