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- Tasks: Join a team to design and build AI virtual agents for customer support.
- Company: Innovative tech company focused on cutting-edge AI solutions.
- Benefits: Enjoy flexible work options, competitive salary, and professional development opportunities.
- Why this job: Be at the forefront of AI technology, making a real impact in customer interactions.
- Qualifications: Degree in relevant field; expertise in ML algorithms and LLMs required.
- Other info: Collaborate with diverse teams and foster creativity in a dynamic environment.
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
Familiarise yourself with the latest advancements in Gen AI and LLMs. Understanding the nuances of prompting, fine-tuning, and evaluation will give you a significant edge during discussions with our team.
✨Tip Number 2
Showcase your hands-on experience with AWS and Azure services. Be prepared to discuss specific projects where you've utilised tools like SageMaker or Azure ML, as this will demonstrate your practical knowledge.
✨Tip Number 3
Highlight your engineering skills, particularly in Python and CI/CD practices. Being able to articulate your experience with GitHub Actions or Azure DevOps will resonate well with our technical requirements.
✨Tip Number 4
Prepare to discuss your approach to workflow automation across the ML lifecycle. Sharing examples of how you've automated processes from data ingestion to model deployment will showcase your ability to enhance efficiency.
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with LLMs and AI technologies. Emphasise your hands-on experience with AWS, Azure, and any specific projects that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data science. Discuss how your skills in mathematics, ML algorithms, and engineering can contribute to building Gen AI virtual agents. Be specific about your achievements and how they relate to the role.
Showcase Relevant Projects: If you have worked on projects involving CI/CD for ML/LLM, containerisation, or workflow automation, make sure to include these in your application. Provide links to your GitHub or portfolio where applicable to demonstrate your practical experience.
Highlight Soft Skills: Don't forget to mention your personal attributes such as communication skills, stakeholder management, and project management experience. These are crucial for collaborating with product and engineering teams, as well as for effective documentation.
How to prepare for a job interview at ISx4
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with LLMs and classical ML algorithms. Highlight specific projects where you've implemented these technologies, especially in relation to AWS or Azure services.
✨Demonstrate Problem-Solving Skills
Expect to face scenario-based questions that assess your ability to design and build AI-powered interactions. Think through your approach to creating context-aware, multi-channel self-service experiences.
✨Communicate Clearly
Since clear communication is key for this role, practice explaining complex technical concepts in simple terms. Be ready to discuss how you manage stakeholder expectations and document processes effectively.
✨Prepare for Collaboration Questions
This position requires close collaboration with product and engineering teams. Prepare examples of how you've successfully worked in cross-functional teams and fostered creativity around frameworks and models.
