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For Companies At a Glance
- Tasks: Lead the design and delivery of AI solutions that create real business value.
- Company: Emerging health tech company revolutionising digital care with AI.
- Benefits: Competitive salary, remote work, and a chance to shape the engineering culture.
- Why this job: Join a mission-driven team and make a significant impact in healthcare technology.
- Qualifications: 6+ years in software engineering and 4+ years in ML/AI model deployment.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
The predicted salary is between 48000 - 72000 £ per year.
About the Company
Our client is an emerging health technology company using AI to modernise digital care and pharmacy infrastructure. Our platform connects clinical operations with intelligent, patient-focused experiences - removing friction, improving coordination, and enabling more personalised care at scale. Building a collaborative, mission-driven team that values creativity, ownership, and innovation. You’ll join at a formative stage, helping define both our AI systems and the engineering culture that powers them.
The Opportunity
As a Senior AI Engineer, you’ll lead the design and delivery of production-grade AI solutions that drive real business value. This is a hands-on, end-to-end role - from architecture and model development to deployment and optimisation. You’ll work closely with product, engineering, and operations teams (and occasionally with enterprise clients) to identify opportunities, translate needs into scalable AI solutions, and bring models into production.
What You’ll Do
- Design and deploy AI systems across areas like personalisation, forecasting, and information retrieval
- Build and maintain robust data pipelines, model training workflows, and monitoring systems
- Collaborate cross-functionally to apply ML/AI to real-world business problems
- Develop tooling and automation for CI/CD, model serving, and A/B testing
- Prototype quickly and scale successful experiments into production-ready systems
What You’ll Bring
- 6+ years of software engineering experience
- 4+ years building and deploying ML/AI models in production
- Proficiency in Python (pandas, scikit-learn, PyTorch, etc.)
- Experience with modern backend stacks (TypeScript, Node.js, Go, or similar)
- Strong understanding of ML principles and model evaluation
- Experience with cloud-based model deployment (GCP preferred)
- Familiarity with containerised workflows (Docker, serverless) and MLOps tools (MLflow, Vertex AI, SageMaker)
- Excellent communication and collaboration skills in a remote-first team
- Willingness to travel occasionally for in-person collaboration or client work
Nice to Have
- Experience with retrieval-augmented generation (RAG) or foundation models
- Exposure to NLP, recommendation systems, or time series forecasting
- Familiarity with streaming architectures and experimentation platforms
- Understanding of healthcare data standards (HIPAA, FHIR)
- Interest in ethical AI and explainability
Senior AI Engineer employer: Nexia
Contact Detail:
Nexia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that Senior AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that demonstrate your ability to solve real-world problems. We want to see your hands-on experience, so make sure to highlight any production-grade solutions you've developed.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of ML principles. We recommend practicing common algorithms and data structures, as well as being ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search. Let’s get you into that dream role together!
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI shine through! We want to see how your experience aligns with our mission to modernise digital care. Share specific projects or achievements that highlight your skills and passion for the field.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Senior AI Engineer role. Highlight relevant experiences, especially those involving ML/AI models and production deployment. We love seeing how you can connect your background to what we do at StudySmarter!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured documents that are easy to read. Use bullet points where necessary and avoid jargon unless it’s relevant to the role. Remember, clarity is key in showcasing your skills!
Apply Through Our Website: Don’t forget to apply 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 team at this exciting stage of growth!
How to prepare for a job interview at Nexia
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI principles and model evaluation. Be ready to discuss your experience with ML/AI models, especially in production. They’ll want to hear about specific projects you've worked on, so have some examples at the ready!
✨Showcase Your Collaboration Skills
Since this role involves working closely with product, engineering, and operations teams, be prepared to talk about how you've successfully collaborated in the past. Share examples of cross-functional projects and how you contributed to their success.
✨Demonstrate Your Technical Proficiency
Familiarise yourself with the tech stack mentioned in the job description, especially Python libraries like pandas and PyTorch. If you’ve worked with cloud-based deployments or containerised workflows, be ready to discuss those experiences in detail.
✨Be Ready for Real-World Applications
Think about how you can apply AI to solve real business problems. Prepare to discuss potential opportunities you see within the company’s focus areas, like personalisation or forecasting, and how you would approach them.
