Lead Data Scientist -Platform AI Acceleration

Glasgow Source: WhatJobs

See advert for pay

Overview

In this role you lead the design, build, and operation of production-grade ML and Generative AI services within the Applied AI/ML team. You will steer technical direction across workstreams, stay close to code and architecture, and ensure secure, reliable delivery at enterprise scale. You’ll mentor engineers, define standards, and drive AI adoption across Infrastructure Platforms to address priority use cases. This is a hands-on leadership position shaping AI engineering at scale in a secure, enterprise environment.

Responsibilities

Analyze large datasets to extract insights and inform decisions
Evaluate and harden AI use cases on enterprise platforms with automated data profiling and quality checks
End-to-end model development across ML, deep learning, and LLM-based approaches including training, tuning, calibration, and failure-mode analysis
Co-develop and implement LLM-based models to solve complex operational challenges
Ship reusable assets (playbooks, templates, reference implementations) and improve them from production telemetry and incidents
Collaborate with wider technology groups to translate business needs into technical solutions
Define standards to ensure regulatory and data-privacy considerations are embedded in system design

Key requirements

Post Graduate qualification (Masters or PhD) in Data Science, Computer Science, or Mathematics
Hands-on production ML/AI system development across statistics, ML, deep learning, and LLMs
Strong grounding in statistics, probability, and experimental design
Deep experience with PyTorch and/or TensorFlow, scikit-learn, Hugging Face Transformers
Distributed training and scalable model serving experience
Experience deploying/operating models in cloud production environments (training/tuning workflows, inference, monitoring)
Strong knowledge of LLMs/SLMs, including fine-tuning, deployment, and cost/latency considerations
Hands-on design/operation of RAG systems with grounding controls
Experience with agentic AI, tool calling, orchestration patterns, guardrails, and safe outputs