Principal ML Architect (Mysuru)

Principal ML ArchitectSkip to main content#Principal ML Architect page is loaded## Principal ML ArchitectApplylocations: Bengaluru Campus 31time type: Full timeposted on: Posted Todaytime left to apply: End Date: June 2, 2026 (4 days left to apply)job requisition id: 542361Welcome 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 current 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, evolve, and assure the ML platform architecture, including experimentation, training, deployment, and monitoring capabilities.* Ensure ML solutions are scalable, reusable, resilient, and cost‐efficient by design.* Embed MLOps principles into architecture standards to enable reliable, production‐grade ML delivery.**Responsible AI, Security & Governance*** Embed Responsible AI principles, data privacy, and security controls into ML architectures by default.* Ensure alignment with enterprise architecture governance, design assurance, and risk management processes.* Enable full model lifecycle governance, including traceability, explainability, auditability, and monitoring.* Experience designing secure, private network-based architecture using vnets and private endpoints in Azure.**Stakeholder Partnership & Influence*** Translate complex business, product, and analytical needs into clear, actionable ML architectural designs.* Act as the architectural bridge between delivery teams, ML platforms, and enterprise data and cloud architecture.* Shape AI and ML strategy through hands‐on technical leadership and architectural thought leadership.**Coaching & Community Contribution*** Mentor senior ML engineers and data scientists, raising architectural maturity and engineering quality.* Contribute to internal Data, AI, and Architecture communities of practice.* Champion modern ML technologies, emerging architectures, and industry best practices.**Qualifications and skills****Essential*** Deep expertise in end‐to‐end machine learning architecture, spanning model development, production deployment, and operational lifecycle management.* Strong architectural understanding of data engineering, feature engineering, and ML pipelines, enabling reliable, scalable model development and consumption.* Proven experience designing and assuring cloud‐native ML solutions on enterprise platforms (e.g. **Azure, Databricks**), aligned to data, security, and platform standards.* Advanced knowledge of MLOps practices, including CI/CD for ML, model monitoring, lifecycle governance, and operational resilience.* Drive end-to-end deployment of advanced analytics by applying deep expertise in **time series, segmentation, and Bayesian Regression modelling frameworks**.* Expertise in Generative AI design patterns, including Large Language Models-**LLMs**, Retrieval Augmented Generation-**RAG**, **Vector Databases**, token optimization and Agentic AI, with experience designing enterprise grade GenAI solutions.* Advanced programming skills in **Python, SQL, Spark**, containerized deployments, message queuing systems with experience building scalable, production grade ML systems.* Demonstrated experience designing, integrating, and maintaining scalable **RESTful APIs** to deploy machine learning models into production* Demonstrated ability to operate as a senior Individual Contributor, providing architectural authority, technical leadership, and governance without line management responsibility**Preferred*** 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.**Education & Qualifications*** Master’s degree in computer science, Data Science, Engineering, Mathematics or a related discipline. A master’s degree or PhD is advantageous.**Experience Requirement*** 10+ years’ experience across data, analytics or engineering roles, with significant depth in machine learning and AI. Demonstrated experience operating at Principal or Architect level, owning complex ML architectures end to end.**Job Posting End Date**2026-06-02 #J-18808-Ljbffr Apply on Kit Job: kitjob.in/job/4n6bbx