Principal Data Scientist

JR United Kingdom; Sheffield; On-site; GBP 150,000 - 200,000; Full time

Job summary

A dynamic tech company in Sheffield is seeking a Principal Data Scientist to design and implement Gen AI virtual agents. The role requires expertise in ML algorithms, LLMs, and significant experience with AWS and Azure. The ideal candidate will cultivate creativity in collaboration with product and engineering teams. This position offers opportunities for professional growth and the chance to work on cutting-edge technology.

Qualifications

• Proven expertise in mathematics and classical ML algorithms.
• Hands-on with AWS and Azure services for data/ML.
• Strong engineering skills in Python, APIs, containers, Git.

Responsibilities

• Design and build client-specific GenAI/LLM virtual agents.
• Enable orchestration, management, and execution of AI-powered interactions.
• Develop CI/CD pipelines for ML/LLM and automate workflows.

Skills

Mathematics expertise

Classical ML algorithms

LLMs knowledge

Python

CI/CD (GitHub Actions/Azure DevOps)

Infrastructure as Code (Terraform/CloudFormation)

Education

Relevant primary level degree

MSc or PhD

Tools

AWS services

Azure services

Kubernetes

Job description

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Principal Data Scientist, sheffield, south yorkshire

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Client:

ISx4

Location:

sheffield, south yorkshire, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

2

Posted:

26.08.2025

Expiry Date:

10.10.2025

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Job Description:

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
• 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
• 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.