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Senior Engineer - Machine Learning Operations

GlobalFoundries

Senior Engineer - Machine Learning Operations

GlobalFoundries

MYS - Penang

·

On-site

·

Full-time

·

1w ago

Required Skills

Python

Java

SQL

MLOps

Kubernetes

Docker

About Global Foundries

Global Foundries is 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, Global Foundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visit www.gf.com.

Your Job:

  • Take ML models/algorithms from conception to production, by designing and implementing ML microservices and pipelines in production environment.

  • Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain.

  • This can include monitoring for data drift, triggering model retraining and setting up rollbacks.

  • Maintain and continuously optimize live productive ML services with a focus on scalability, availability, and reliability.

  • Strive for automation and cloud operation readiness.

  • Collaborate with data scientists and data engineers to deliver ML models in productive services.

  • Stay updated with the latest trends and technologies in AI/ML, GenAI and MLOps to drive innovation and system enhancements.

Required Qualifications:

  • Bachelor's degree in computer science or equivalent. A minimum of 4 years' experience in software engineering or machine learning engineering is preferred.

  • Strong programming skills in Python, Java and SQL variants, with knowledge of design patterns, code optimization, and object-oriented design.

  • Proficiency in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms

  • Familiar with Kubernetes and Docker, including installation, deployment, configuration and optimization.

  • Good understanding of ML frameworks such as Tensor Flow, Keras, Py Torch.

  • Experience in web development skills such as HTML, Javascript, CSS is a big plus.

  • Knowledge of AWS cloud platform would be an advantage.

Global Foundries 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 Global Foundries are conditioned upon the successful completion of background checks, medical screenings as applicable and subject to the respective local laws and regulations.

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

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About GlobalFoundries

GlobalFoundries

A full-service semiconductor foundry that manufactures integrated circuits in high volume.

10,001+

Employees

Santa Clara

Headquarters

Reviews

3.4

9 reviews

Work Life Balance

3.2

Compensation

3.1

Culture

3.4

Career

2.8

Management

2.9

65%

Recommend to a Friend

Pros

Good learning experience and knowledge sharing

Decent pay and benefits

Diverse and welcoming culture

Cons

Limited career growth opportunities

Management and communication issues

Cost cutting and layoffs

Salary Ranges

0 data points

Junior/L3

Junior/L3 · Venture Capitalist

0 reports

$89,550

total / year

Base

-

Stock

-

Bonus

-

$76,118

$102,983

Interview Experience

51 interviews

Difficulty

3.3

/ 5

Duration

14-28 weeks

Offer Rate

36%

Experience

Positive 68%

Neutral 20%

Negative 12%

Interview Process

1

Phone Screen

2

Technical Interview

3

Hiring Manager

4

Team Fit

Common Questions

Technical skills

Past experience

Team collaboration

Problem solving