Senior Machine Learning Engineer

Job Description

**Role Overview:**Welcome to Haleon, a purpose-driven consumer company dedicated to improving everyday health for millions of people. As a Senior Machine Learning Engineer, you will play a crucial role in leading the deployment of machine learning solutions to transform the integrated business planning process at Haleon. Your responsibilities will include designing and implementing end-to-end machine learning pipelines for various applications.**Key Responsibilities:**- Lead the deployment of ML solutions on the enterprise infrastructure following ML engineering standards and best practices.- Manage the lifecycle of data science/machine learning models, including monitoring, data gathering for retraining, and updates.- Implement ML engineering best practices like coding standards, code reviews, and automated testing.- Define and implement metrics to evaluate the functional performance and computational resource efficiency of ML and AI components.- Coordinate and manage competing priorities across a portfolio of projects.- Influence and collaborate with cross-functional teams, including data scientists, data engineers, and business stakeholders.**People and Team Management:**- Contribute to a collaborative team culture with a focus on ownership, initiative, and responsibility.- Develop ML engineering standards and mentor colleagues within the ML Engineering Team.- Manage a team of up to 3 Machine Learning Engineers.**Qualifications & Skills:**- BSc, MSc, or PhD degree in mathematics, computer science, or a related scientific discipline.- 5-10 years of industry experience implementing machine learning engineering pipelines on large datasets.- Strong understanding of ML engineering best practices.- Collaboration skills, ability to manage ambiguity, and make informed decisions.- Experience with deploying machine learning solutions on enterprise infrastructure.- Strong programming skills in Python or similar languages.**Highly Desirable Qualifications & Skills:**- Experience with cloud-based infrastructure like Azure, AWS, or GCP.- Familiarity with containerization and orchestration tools such as Docker and Kubernetes.- Understanding of software engineering principles, clean code, and testing.- Knowledge of DevOps practices, CI/CD pipelines, and tools like Ansible or Terraform.- Strong problem-solving skills and ability to debug complex issues.- Excellent communication skills and collaboration with cross-functional teams.- Familiarity with monitoring and logging tools like Grafana, Prometheus, and ELK Stack.- Knowledge of security best practices in machine learning engineering.*Note: Job Posting End Date - 2026-03-24***Equal Opportunities:**Haleon is committed to fostering an inclusive culture that values and respects diverse backgrounds and views, ensuring all employees feel they belong.**Adjustment or Accommodations Request:**If you require reasonable adjustments or accommodations during the application process, please inform your recruiter to receive the necessary support.*Note to candidates:*The recruitment team at Haleon will contact you using a Haleon email account (@haleon.com). If you have any doubts about the authenticity of an email, please reach out to verify. **Role Overview:**Welcome to Haleon, a purpose-driven consumer company dedicated to improving everyday health for millions of people. As a Senior Machine Learning Engineer, you will play a crucial role in leading the deployment of machine learning solutions to transform the integrated business planning process at Haleon. Your responsibilities will include designing and implementing end-to-end machine learning pipelines for various applications.**Key Responsibilities:**- Lead the deployment of ML solutions on the enterprise infrastructure following ML engineering standards and best practices.- Manage the lifecycle of data science/machine learning models, including monitoring, data gathering for retraining, and updates.- Implement ML engineering best practices like coding standards, code reviews, and automated testing.- Define and implement metrics to evaluate the functional performance and computational resource efficiency of ML and AI components.- Coordinate and manage competing priorities across a portfolio of projects.- Influence and collaborate with cross-functional teams, including data scientists, data engineers, and business stakeholders.**People and Team Management:**- Contribute to a collaborative team culture with a focus on ownership, initiative, and responsibility.- Develop ML engineering standards and mentor colleagues within the ML Engineering Team.- Manage a team of up to 3 Machine Learning Engineers.**Qualifications & Skills:**- BSc, MSc, or PhD degree in mathematics, computer science, or a related scientific discipline.- 5-10 years of industry experience implementing machine learning engineering pipelines on large datasets.- Strong understanding of ML engineering best

Keyskills :
Machine LearningPythonData ScienceContainerizationML EngineeringCloudbased InfrastructureDistributed Computing SystemsOrchestration ToolsSoftware Engineering PrinciplesDevOps Practices