Process Engineer

GlobalFoundries; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

GlobalFoundries in Singapore is pursuing Industry 4.0 initiatives by leveraging data analytics, ML, and AI to predict equipment failure and enable just-in-time maintenance. We seek a passionate engineer with computer science/data science background to join our Digital Manufacturing journey and contribute to a high-performing team.

The role focuses on developing ML applications, collaborating with process/equipment teams, and deploying models into production with robust documentation and

Qualifications

• Degree in Computer Science/Engineering or related field with 3 years of working experience.
• Strong theoretical and practical knowledge of key areas in Artificial Intelligence.
• Proficiency in programming languages such as Python.
• Experience with Relational Databases; MySQL, PostgreSQL, Oracle
• Knowledge of machine learning frameworks such as Sagemaker Studio, PyTorch, Tensorflow, Keras.
• Independent and good experience in troubleshooting application bugs and performance issues.
• Team player with positive work attitude and good interpersonal and communication skills.

Responsibilities

• Work in close collaboration with process and equipment team.
• Perform data analytics which include analyzing sensor data, process recipe and historical trend of equipment performance.
• Research and implement appropriate ML algorithms and tools.
• Conduct machine learning tests and experiments with appropriate datasets and data representation methods.
• Develop machine learning applications according to requirements such as tool type, recipe, and equipment constraint.
• Integrating proven machine learning solution into maintenance system with statistical analysis and fine-tuning machine learning models.
• Establish business processes necessary to deploy and upkeep the machine learning model in production, as well as their documentation according to quality standards.
• Scale up machine learning solution to other equipment.
• Ensure continuous knowledge exchange on best known methods and improvement levers across geographical locations (e.g. Fab 1/7/8/9).

Skills

Python programming

Artificial intelligence fundamentals

Troubleshooting

Team player

Communication skills

Education

Bachelor's degree in Computer Science/Engineering

Tools

Sagemaker Studio

PyTorch

TensorFlow

Keras

Job description

About GlobalFoundries

GlobalFoundriesis a leading full-service semiconductor foundry providing a unique combination of design, development, and fabrication services to some of the world’s most inspired technology companies. With a global manufacturing footprint spanning three continents, GlobalFoundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visitwww.gf.com.

Summary of Role

As GlobalFoundries Singapore is embarking Industry 4.0, leveraging the technology advancement involves using data analysis, machine learning and AI to predict equipment failure to perform just in time maintenance. This “Predictive Maintenance” is one of key focus in our digital manufacturing initiatives. We are looking for passionate engineer with computer engineering/data science background to join us and be part of the high performing team in GlobalFoundries Digital Manufacturing journey.

Essential Responsibilities include:

• Work in close collaboration with process and equipment team.
• Perform data analytics which include analyzing sensor data, process recipe and historical trend of equipment performance.
• Research and implement appropriate ML algorithms and tools.
• Conduct machine learning tests and experiments with appropriate datasets and data representation methods.
• Develop machine learning applications according to requirements such as tool type, recipe, and equipment constraint.
• Integrating proven machine learning solution into maintenance system with statistical analysis and fine-tuning machine learning models.
• Establish business processes necessary to deploy and upkeep the machine learning model in production, as well as their documentation according to quality standards.
• Scale up machine learning solution to other equipment.
• Ensure continuous knowledge exchange on best known methods and improvement levers across geographical locations (e.g. Fab 1/7/8/9).

Required Qualifications:

• Degree in Computer Science/Engineering or related field with 3 years of working experience.
• Strong theoretical and practical knowledge of key areas in Artificial Intelligence.
• Proficiency in programming languages such as Python.
• Experience with Relational Databases; MySQL, PostgreSQL, Oracle
• Knowledge of machine learning frameworks such as Sagemaker Studio, PyTorch, Tensorflow, Keras.
• Independent and good experience in troubleshooting application bugs and performance issues.
• Team player with positive work attitude and good interpersonal and communication skills.

GlobalFoundries is an equal opportunity employer, cultivating a diverse and inclusive workforce. We believe having a multicultural workplace enhances productivity, efficiency and innovation whilst our employees feel truly respected, valued and heard.

As an affirmative employer, all qualified applicants are considered for employment regardless of age, ethnicity, marital status, citizenship, race, religion, political affiliation, gender, sexual orientation and medical and/or physical abilities.

All offers of employment with GlobalFoundries are conditioned upon the successful completion of background checks, medical screenings as applicable and subject to the respective local laws and regulations.

To ensure that we maintain a safe and healthy workplace for our GlobalFoundries employees, please note that offered candidates who have applied for jobs in Singapore will have to be fully vaccinated prior to their targeted start date. For new hires, the appointment is contingent upon the provision of a copy of their COVID-19 vaccination document, subject to any written request for medical or religious accommodation.