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Johnson & Johnson

Machine Learning Engineer

Johnson & Johnson
Singapore · Full-time · Not Applicable

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function

Data Analytics & Computational Sciences

Job Sub Function

Data Science

Job Category

Scientific/Technology

All Job Posting Locations:

SG003 Science Park Drive (Ascent)

Job Description

The APAC Business Technology Team within Innovative Medicine (IM) 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), patients and for IM. There are many ways to explore and analyze data, and this powers the excitement and passion of data scientists at IM as many business units are eager to use the data to build business value.

Specifically, You Will

As a Regional Machine Learning Engineer, you will work closely with senior engineers, data scientists, and business teams to build machine learning solutions for various projects across the region. You will gain hands-on experience in developing, deploying, and optimizing machine learning models while working in a collaborative environment. Your contributions will support key focus areas, including patient/payer analytics, commercial strategy, and patient support program analytics.

Key Responsibilities

  • Assist in developing and deploying end-to-end machine learning applications to support business needs.
  • Work with data scientists and engineers to build scalable ML pipelines and automation processes.
  • Support the evaluation and integration of various data science tools, platforms, and services.
  • Write clean, maintainable, and efficient code to ensure smooth deployment of ML models.
  • Collaborate with cross-functional teams (business, technology, and product) to understand requirements and contribute to AI-driven solutions.
  • Learn and apply best practices in machine learning, software engineering, and cloud computing.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, or a related field.
  • 2 years or above experience in machine learning, data science, or software engineering.
  • Strong analytical, problem-solving, and communication skills.
  • Experience with Python for machine learning and data science applications.
  • Familiarity with common ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Basic understanding of ML model development and deployment.
  • Exposure to cloud platforms (AWS, Azure) and big data technologies (e.g., Spark, Databricks) is a plus.
  • Experience with version control (Git), CI/CD tools, and workflow automation (Airflow, Jenkins) is an advantage.
  • Ability to work collaboratively in a fast-paced, multi-disciplinary team.

Why Join Us?

  • Work in a dynamic and innovative environment at the intersection of healthcare and AI.
  • Learn from seasoned professionals and grow your expertise in machine learning, big data, and AI-driven solutions.
  • Gain hands-on experience in real-world AI applications that have a direct impact on patients, HCPs, and business strategy.
  • Be part of a diverse, collaborative, and forward-thinking organization.

If you are passionate about AI, machine learning, and data-driven problem-solving, we would love to hear from you!

Key Skills

Ranked by relevance

machine learning ai big data cloud artificial intelligence tensorflow jenkins pytorch python spark cicd git aws
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Posted
Mar 10, 2025
Type
Full-time
Level
Not Applicable
Location
Singapore

Industries

Hospitals Health Care

Categories

Engineering Information Technology

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