Senior Machine Learning Engineer

4 weeks ago

Bangalore, India Haleon Full time
About the Role

Haleon is a world-leading consumer health company that is shaping the future of everyday health for billions of people. We're a company that is in control of our own destiny, with a unique culture that is built on deep human understanding and trusted science.

We're looking for a Senior Machine Learning Engineer to join our team and contribute to a strategic digital programme that will transform our integrated business planning process. As a key member of our team, you will be responsible for designing and implementing end-to-end machine learning pipelines for various responsibilities.

Key Responsibilities
  • Lead the deployment of machine learning solutions on our enterprise infrastructure, adhering to machine learning engineering standards and best practices.
  • Manage the entire lifecycle of data science/machine learning models, including monitoring, data gathering for retraining, and updates.
  • Implement machine learning engineering best practices, such as coding standards, code reviews, and automated testing.
  • Define and implement metrics to evaluate the functional performance and computational resource efficiency of machine learning and AI components.
  • Coordinate and manage competing priorities across a portfolio of projects.
Requirements
  • BSc, MSc or PhD degree in mathematics, computer science, or another scientific discipline that provides solid foundations on relevant aspects of data science.
  • 5-10 years of industry experience with proven experience implementing machine learning engineering pipelines on large datasets.
  • Strong understanding of machine learning engineering best practices.
  • Strong collaboration skills and comfortable working with ambiguity, making quick, informed decisions considering trade-offs.
  • Experience with deploying machine learning solutions on enterprise infrastructure.
  • Strong programming skills in Python or similar programming languages.
Desirable Qualifications and Skills
  • Strong experience with cloud-based infrastructure and distributed computing systems, such as Azure, AWS, or GCP.
  • Experience with containerization and orchestration tools, such as Docker and Kubernetes.
  • Understanding of software engineering principles, such as modular design, clean code, and testing.
  • Familiarity with DevOps practices and tools, such as continuous integration and deployment (CI/CD) pipelines and configuration management tools like Ansible or Terraform.
  • Excellent problem-solving skills and the ability to debug complex issues in production environments.
  • Strong communication skills and the ability to collaborate with cross-functional teams.
  • Familiarity with monitoring and logging tools, such as Grafana, Prometheus, and ELK Stack.
  • Knowledge of security best practices in machine learning engineering.

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