Customer Engineer - Data Science / ML DevOps Internship

Who We Are

Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

What We Offer

Location: Singapore, SGP

You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company.

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go.

Project Description

Predictive models provide value for field service engineers to move from break-fix maintenance to a more proactive maintenance approach. As the number of models increases, model governance and management become crucial to sustain the value of the models to end users. The intern will study the existing approach and propose improvements to the current situation. The intern will collaborate with data scientists and equipment experts to pilot a framework for end-to-end model management, along with documentation of best practices.

Preferred Discipline

• Data Science & Analytics
• Computer Engineering

Desired Skills Required

• Programming in Python
• Basic knowledge of machine learning and data analysis
• Understanding of physics principles related to sensing and measurement
• Familiarity with data visualization tools
• Ability to interpret experimental results and draw conclusions
• Familiarity with machine learning workflows and ML DevOps best practices

Learning Outcome

The intern will gain practical experience in process improvement methodologies and digital transformation within an operational setting. They will develop skills in stakeholder engagement, data collection, and analysis, and learn how to translate process insights into actionable recommendations. They will gain firsthand experience applying industrial engineering methodologies in a live production environment, present data-backed recommendations to stakeholders, and understand how systematic analysis contributes to operational efficiency and lean manufacturing goals.

Additional Information

• Time Type: Full time
• Employee Type: Intern / Student
• Travel: No
• Relocation Eligible: No