Haleon
PrincipalMachineLearningArchitect
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“Principal Machine Learning Architect at Haleon. Skills: Machine Learning Architecture, MLOps, Generative AI, Python. Own and govern end‑to‑end ML architectures. Define and maintain standardised ML architecture patterns”
What They're Looking For.
Must Have
Deep expertise in end‑to‑end machine learning architecture, architectural understanding of data engineering, feature engineering, ML pipelines, Proven experience designing and assuring cloud‑native ML solutions on enterprise platforms (e. g. Azure, Databricks), Advanced knowledge of MLOps practices, Drive end‑to‑end deployment of advanced analytics, deep expertise in time series, segmentation, Bayesian Regression modelling frameworks, Expertise in Generative AI design patterns, Large Language Models-LLMs, Retrieval Augmented Generation-RAG, Vector Databases, token optimization, Agentic AI, experience designing enterprise grade GenAI solutions, Advanced programming skills in Python, SQL, Spark, containerized deployments, message queuing systems, experience building scalable, production grade ML systems, Demonstrated experience designing, integrating, and maintaining scalable RESTful APIs, Demonstrated ability to operate as a senior Individual Contributor, providing architectural authority, technical leadership, governance without line management responsibility, 10+ years’ experience across data, analytics or engineering roles, significant depth in machine learning and AI, Demonstrated experience operating at Principal or Architect level, owning complex ML architectures end to end
Nice to Have
Experience in regulated or high-risk ML environments, Exposure to multiple ML domains (predictive, NLP, optimisation, computer vision), Familiarity with enterprise data platforms and analytics ecosystems, A master’s degree or PhD is advantageous
What You'll Do.
Own and govern end‑to‑end ML architectures
Define and maintain standardised ML architecture patterns
Serve as senior ML technical authority
and assure ML platform architecture
Ensure ML solutions are scalable
Embed MLOps principles into architecture standards
Embed Responsible AI principles
Ensure alignment with enterprise architecture governance
Enable full model lifecycle governance
Experience designing secure network architecture
Translate business needs into ML architectural designs
Act as architectural bridge between teams
Shape AI and ML strategy
Mentor senior ML engineers
Contribute to internal communities
Champion modern ML technologies
How You'll Work.
Team & Collaboration
Act as the architectural bridge between delivery teams, ML platforms, and enterprise data and cloud architecture.
Full Job Description
Welcome to Haleon. We’re a purpose-driven, world-class consumer company putting everyday health in the hands of millions. In just three years since our launch, we’ve grown, evolved and are now entering an exciting new chapter – one filled with bold ambitions and enormous opportunity. Our trusted portfolio of brands – including Sensodyne®, Panadol®, Advil®, Voltaren®, Theraflu®, Otrivin®, and Centrum® – lead in resilient and growing categories. What sets us apart is our unique blend of deep human understanding and trusted science. Now it’s time to fully realise the full potential of our business and our people. We do this through our Win as One strategy. It puts our purpose – to deliver better everyday health with humanity – at the heart of everything we do. It unites us, inspires us, and challenges us to be better every day, driven by our agile, performance-focused culture. **About the role** The **Principal Machine Learning Architect** is accountable for defining, governing and evolving end-to-end Machine Learning architectures that enable scalable, secure and responsible AI solutions across the enterprise. The role translates business and scientific use cases into implementable ML architectures covering data, feature engineering, model development, deployment, monitoring and lifecycle management. The ML Architect sets architectural standards for ML platforms and solutions, ensures alignment with enterprise data and cloud architectures, and enables delivery teams to industrialise ML safely and efficiently. **Key responsibilities** **ML Architecture & Technical Leadership** * Own and govern end‑to‑end ML architectures for complex, high‑impact AI initiatives across the enterprise. * Define and maintain standardised ML architecture patterns covering training, inference, batch, and real‑time use cases. * Serve as the senior ML technical authority, driving architectural decision‑making and managing key design trade‑offs. **Platform & Lifecycle Enablement** * Define, evo
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