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Machine Learning Engineer for Digital Manufacturing

Dresden

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Employment
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Apply at Globalfoundries

What you’ll work on

Full posting
  • Support the AI Integration Team in developing and deploying AI/ML models.

  • Work with highly complex data for feature development using AI/ML models.

  • Work closely with teams in Digital Manufacturing and other stakeholders to define project objectives, deliverables, and timelines.

From the employer’s posting
Responsibilities Support the AI Integration Team in developing and deploying AI/ML models. Work with highly complex data for feature development using AI/ML models.
Support the AI Integration Team in developing and deploying AI/ML models. Work with highly complex data for feature development using AI/ML models. Work closely with teams in Digital Manufacturing and other stakeholders to define project objectives, deliverables, and timelines.
Work with highly complex data for feature development using AI/ML models. Work closely with teams in Digital Manufacturing and other stakeholders to define project objectives, deliverables, and timelines. Adapt to evolving technologies and learn new tools and techniques. Committed to stay updated with the State-of-the-Art advancements in AI/ML.

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree in engineering, Computer Science, or related quantitative field.
  • Proficiency in AI/ML techniques and frameworks (incl.
  • Familiarity with MLOps, CI/CD pipelines for ML, and monitoring tools for model performance and drift detection.
  • Practical experience with AWS services for ML deployment.
  • Deep understanding of data pipelines, and data quality principles.
  • Excellent communication and collaboration skills.

Preferred experience

  • Master's degree in engineering, Computer Science, or related quantitative field.
  • Ability to enforce data quality standards and maintain data dictionaries.
  • Experience with data governance frameworks and guidelines.
Qualification wording
Bachelor's degree in engineering, Computer Science, or related quantitative field.
Proficiency in AI/ML techniques and frameworks (incl. PyTorch, Scikit-Learn, LangChain etc.), and model deployment strategies.
Familiarity with MLOps, CI/CD pipelines for ML, and monitoring tools for model performance and drift detection.
Practical experience with AWS services for ML deployment.
Deep understanding of data pipelines, and data quality principles.
Excellent communication and collaboration skills.
Master's degree in engineering, Computer Science, or related quantitative field.
Ability to enforce data quality standards and maintain data dictionaries.
Experience with data governance frameworks and guidelines.

Tools in this posting

  • AWS
  • Azure
  • Google Cloud (GCP)
  • scikit-learn
  • PyTorch
Source — Tool mentions in context
- Familiarity with MLOps, CI/CD pipelines for ML, and monitoring tools for model performance and drift detection. - Practical experience with AWS services for ML deployment. - Deep understanding of data pipelines, and data quality principles.
- Master's degree in engineering, Computer Science, or related quantitative field. - Extensive experience with cloud platforms (AWS, Azure, Google Cloud) for building and deploying AI solutions. - Ability to enforce data quality standards and maintain data dictionaries.
- A minimum of 2 years of experience in ML engineering or Applied AI. - Proficiency in AI/ML techniques and frameworks (incl. PyTorch, Scikit-Learn, LangChain etc.), and model deployment strategies. - Familiarity with MLOps, CI/CD pipelines for ML, and monitoring tools for model performance and drift detection.

Job description

View original posting ↗

About GF 
GlobalFoundries® Inc. (GF®) is one of the world's leading semiconductor manufacturers. GF redefines innovation and semiconductor manufacturing by developing and delivering feature-rich process technology solutions with leading performance in all growth markets. GF offers a unique mix of design, development and manufacturing services. With a talented and diverse team and manufacturing locations in the U.S., Europe and Asia, GF is a trusted technology provider to its global customers. GF employs approximately 13,000 people, including more than 3,000 in Dresden, Germany.

For more information, visit www.gf.com.

 

Introduction 

As an Machine Learning Engineer for Digital Manufacturing, you will be joining the Digital Manufacturing Group and perform a key role within the AI Integration team and assist in the AI/ML/GenAI solutions’ technical requirements. You will help establish best practices for analytics use case development, deployment, scaling, and maintenance of AI/ML projects. 

 

Responsibilities 

  • Support the AI Integration Team in developing and deploying AI/ML models.  

  • Work with highly complex data for feature development using AI/ML models.  

  • Work closely with teams in Digital Manufacturing and other stakeholders to define project objectives, deliverables, and timelines.   

  • Adapt to evolving technologies and learn new tools and techniques. Committed to stay updated with the State-of-the-Art advancements in AI/ML. 

 

Required Qualifications 

  • Bachelor's degree in engineering, Computer Science, or related quantitative field. 

  • A minimum of 2 years of experience in ML engineering or Applied AI. 

  • Proficiency in AI/ML techniques and frameworks (incl. PyTorch, Scikit-Learn, LangChain etc.), and model deployment strategies.  

  • Familiarity with MLOps, CI/CD pipelines for ML, and monitoring tools for model performance and drift detection. 

  • Practical experience with AWS services for ML deployment. 

  • Deep understanding of data pipelines, and data quality principles. 

  • Flexibility and ability to work with ambiguous problems and unstructured data. 

  • Excellent communication and collaboration skills. 

  • Ability to work independently and as part of a cross-functional international team. 

  • Strong problem-solving and analytical skills with a passion for building high-quality solutions.  

 

Preferred Qualifications

  • Master's degree in engineering, Computer Science, or related quantitative field.   

  • Extensive experience with cloud platforms (AWS, Azure, Google Cloud) for building and deploying AI solutions. 

  • Ability to enforce data quality standards and maintain data dictionaries. 

  • Experience with data governance frameworks and guidelines. 

  • Exposure to semiconductor/manufacturing domain. 

 

We Offer 

The position is open-ended and to be filled as soon as possible.

  

Attractive compensation components:   

13th month salary, bonus payments, assistance with relocation to Dresden.  

Flexible working time arrangements:   

Family friendly part-time models, trust flextime, salary conversion into free time  

Diverse opportunities for further development:   

Career stages for every job, internal qualification offers, promotion of external educational qualifications  

Focus on your health:   

On-site gym and beach volleyball court, bike leasing, subsidized employee restaurant  

Corporate culture:   

Cooperation at eye level - everyone is on first name terms with us, budget for individual team events, social commitment via GlobalGives  

  

You can find more benefits in detail at https://gf.com/de/careers/benefits/ 

The job advertisement refers to a position up to job level 6 on the GF career ladder.

This position is part of our employee referral program and will be rewarded with a referral bonus of €2,000 upon successful recruitment.

Information about our benefits you can find here: https://gf.com/careers/opportunities-in-europe/

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on globalfoundries.wd1.myworkdayjobs.com. The employer’s form will show what is required.

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Location & working pattern

Dresden

Focus on your health: On-site gym and beach volleyball court, bike leasing, subsidized employee restaurant Corporate culture:
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Status in our records
Active
First seen by us
Aug 13, 2026
Recorded sightings
37
Last seen by us
Oct 9, 2026

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