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- Tasks: Design and build innovative Gen AI virtual agents for customer support across multiple channels.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Be a key player in shaping the future of AI technology and customer experiences.
- Qualifications: Degree in a relevant field; expertise in ML algorithms and LLMs required.
- Other info: Collaborative environment with a focus on creativity and continuous improvement.
The predicted salary is between 72000 - 108000 £ per year.
You will be part of a team designing and building a Gen AI virtual agent to support customers and employees across multiple channels. You will build and run LLM-powered agentic experiences, owning the design, orchestration, MLOps, and continuous improvement.
- Design & build client-specific GenAI/LLM virtual agents
- Enable the orchestration, management, and execution of AI-powered interactions through purpose-built AI agents
- Design, build and maintain robust LLM powered processing workflows
- Develop cutting edge testing suites related to bespoke LLM performance metrics
- Craft context-aware, multi-channel self-service experiences
- Develop bespoke testing suites and LLM performance metrics
- CI/CD for ML/LLM: automated build/train/validate/deploy pipelines for chatbots and agent services
- IaC – Infrastructure as Code, (Terraform/CloudFormation) to provision scalable cloud for training and real-time inference
- Observability: monitoring, drift detection, hallucination, SLOs, and alerting for model and service health
- Serving at scale: containerised, auto-scaling (e.g., Kubernetes) with low-latency inference
- Data & model versioning; maintain a central model registry with lineage and rollback
- Workflow automation across the ML lifecycle (data ingestion → retraining → deployment)
- Deliver a live performance dashboard (intent accuracy, latency, error rates) and a documented retraining strategy
- Lead and foster creativity around frameworks/models; collaborate closely with product, engineering, and client stakeholders
Qualifications / Experience
- Relevant primary level degree and ideally MSc or PhD
- Proven expertise in mathematics and classical ML algorithms, plus deep knowledge of LLMs (prompting, fine-tuning, RAG/tool use, evaluation)
- Hands-on with AWS and Azure services for data/ML (e.g., Bedrock/SageMaker, Azure OpenAI/Azure ML)
- Strong engineering: Python, APIs, containers, Git; CI/CD (GitHub Actions/Azure DevOps), IaC (Terraform/CloudFormation)
- Scalable Serving Infrastructure: A containerized, auto-scaling environment (e.g., using Kubernetes) to serve the chatbot model with low latency
- Workflow Automation: Automate the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model retraining and deployment
- Live Performance Dashboard: A real-time dashboard displaying key model metrics such as intent accuracy, response latency, and error rates
- Centralized Model Registry: A versioned repository for all trained models, their performance metrics, and associated training data
- Documented Retraining Strategy: An automated workflow and documentation outlining the process for periodically retraining the model on new data
- Experience with Kubernetes, inference optimisation, caching, vector stores, and model registries
- Clear communication, stakeholder management, and a habit of writing crisp technical docs and runbooks
Personal Attributes
- Personal Integrity, Stakeholder Management, Project Management, Agile Methodologies, Automation, Data Visualisation and Analysis.
Principal Data Scientist employer: ISx4
Contact Detail:
ISx4 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to LLMs and AI. It’s a great way to demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to data science and AI. We recommend doing mock interviews with friends or using online platforms.
✨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!
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in LLMs and ML algorithms. We want to see how your experience aligns with the role, so don’t hold back on showcasing your technical prowess!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Principal Data Scientist position. Use keywords from the job description to demonstrate that you understand what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate crisp communication, so avoid fluff and focus on what makes you a great fit for our team.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at ISx4
✨Know Your Stuff
Make sure you brush up on your knowledge of LLMs and classical ML algorithms. Be ready to discuss your hands-on experience with AWS and Azure services, as well as your engineering skills in Python and CI/CD practices. The more specific examples you can provide, the better!
✨Showcase Your Creativity
Since this role involves designing and building Gen AI virtual agents, think about innovative ideas or frameworks you've worked on in the past. Be prepared to share how you foster creativity in your projects and collaborate with stakeholders to bring those ideas to life.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous roles, especially around model performance metrics and workflow automation. Highlight any experience you have with monitoring, drift detection, and maintaining a central model registry, as these are crucial for the position.
✨Communicate Clearly
Strong communication is key! Practice explaining complex technical concepts in a way that's easy to understand. Be ready to discuss how you manage stakeholder expectations and document processes, as clear communication will be vital in this role.
