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Data Analytics & Computational Sciences

Manager - Machine Learning Engineer

  • Titre Manager - Machine Learning Engineer
  • Fonction Data Analytics & Computational Sciences
  • Sous-fonction Data Science
  • Catégorie Principal Scientist, Data Science (ST7)
  • Lieu Singapore
  • Date de mise en ligne
  • Référence 2406199109W
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The APAC Business Technology Team within Johnson & Johnson Innovative Medicine, is looking for an extraordinary machine learning engineer who is passionate about crafting, developing, and fielding data science solutions that drive impact for HCP (Health Care Professional) and patients. 

As the regional machine learning engineer, you will be responsible for designing and building the machine learning engineering solutions across the region. You will leverage your technical expertise, experience, and communication skills to work across business & technology teams productionize innovative data science models and applications. Your technical knowledge and ability to apply them, will be paramount to your success in this role. Focus areas include (but not limited) to patient analytics, commercial strategy, and patient support program analytics. Specifically, you will build end-to-end machine learning pipelines by developing and applying creative solutions that go beyond current tools and work together with data scientist to deliver scalable, reusable, extensible and flexible solution.

  • Deliver end to end machine learning applications for our key projects across the region.
  • Execute the regional machine learning engineering strategy including people, technology, platforms, and process.
  • Collaborate with platform teams and solution architect to evolve our big data platforms and evaluate various data science technologies and services.
  • Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.

You will be someone who stays on the cutting edge of artificial intelligence, data science and software engineering through novel project execution and development of algorithms that improve organizational performance and commercial effectiveness. The role requires both a broad knowledge of existing software development lifecycle, AI algorithms and the creativity to invent and customize when necessary. You will work with matrixed teams across business and technology, and will be part of a dynamic, accomplished organization that will support multiple therapeutic areas.


Build and Own Machine Learning Solutions:

  • Collaborate with data scientist and other technology teams to design and build machine learning engineering solution for the region.
  • Establish and maintain ML pipelines to automate the training, testing, and deployment of AI models
  • Implement CI/CD practices to ensure continuous integration and delivery of AI solutions.
  • Monitor and manage the lifecycle of deployed models, ensuring they meet performance and reliability standards.

Cloud AI Solutions (AWS and Azure):

  • Architect and implement scalable AI solutions on cloud platforms such as AWS and Azure.
  • Utilize cloud services to manage and deploy AI models, ensuring high availability and performance.

Research and Innovation:

  • Stay updated with the latest advancements in data science, cloud technologies, and MLOps practices, and bring them to the team.
  • Drive innovation by exploring new tools, techniques, and methodologies to improve AI capabilities and efficiencies


Required Minimum Education: Bachelor’s degree

Required Years of Related Experience: At least 5 years' professional experience is required with at least 3 years of production grade machine learning model development experience. 

  • Minimum 3 years of experience in Machine Learning and MLOps, developing end-to-end machine learning solutions. Must have proven ability to take solutions to production, while effectively monitoring and maintaining them.
  • Over 6+ years of experience in the software engineering lifecycle as a developer, with a focus on writing production code.
  • Excellent programming skills in Python and proficiency in PySpark.
  • Must have hands-on experience working with software development toolkits and devOps automations like Kubernetes, Airflow, Jenkins, Jira, Confluence, and Git.
  • Strong working knowledge of deep learning and machine learning techniques such as regression, decision trees, Bayesian models, clustering etc.
  • Hands-on experience working with cloud solutions, specifically AWS and Azure.
  • Experience in Databricks, Azure ML, AWS Sagemaker is a plus.
  • Excellent communication skills and a demonstrated ability to collaborate effectively with cross-function teams.
  • Self-motivated and highly driven individual who thrives under ambiguous requirements

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