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- Tasks: Join a team to design and build cutting-edge Gen AI virtual agents for diverse customer interactions.
- Company: Innovative tech company focused on AI solutions for enhancing customer and employee experiences.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology, collaborating with creative minds in a dynamic environment.
- Qualifications: Degree in relevant field; expertise in ML algorithms and LLMs; hands-on experience with AWS/Azure.
- Other info: Ideal for those passionate about AI and eager to make a real impact in the tech industry.
The predicted salary is between 57600 - 84000 £ 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 LLM technologies. Being well-versed in these areas will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Engage with online communities or forums related to data science and AI. Networking with professionals in the field can provide insights into the company culture and expectations, which can be invaluable during your application process.
✨Tip Number 3
Prepare to discuss your hands-on experience with AWS and Azure services. Be ready to share specific examples of how you've used these platforms in past projects, as this will showcase your technical expertise.
✨Tip Number 4
Brush up on your knowledge of CI/CD practices and container orchestration, particularly with Kubernetes. Understanding these concepts will be crucial for demonstrating your ability to manage scalable serving infrastructure effectively.
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 background in mathematics and ML algorithms makes you a perfect fit for designing and building Gen AI virtual agents.
Showcase Technical Skills: Clearly outline your technical skills related to Python, CI/CD, and containerisation. Provide examples of how you've used these skills in past projects, especially in relation to scalable serving infrastructure and workflow automation.
Highlight Collaboration Experience: Since the role involves working closely with product and engineering teams, mention any previous experiences where you successfully collaborated with stakeholders. This could include project management or agile methodologies you've employed.
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 experiences and be ready to explain your thought process.
✨Communicate Clearly and Effectively
Since the role involves stakeholder management, practice articulating complex technical concepts in a simple manner. Prepare to discuss how you would document processes and create runbooks for your projects.
✨Prepare for Collaborative Discussions
This position requires close collaboration with product and engineering teams. Be ready to share examples of how you've successfully worked in cross-functional teams and fostered creativity around frameworks and models.
