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Company: AMD
Location: Singapore, Singapore
Career Level: Mid-Senior Level
Industries: Technology, Software, IT, Electronics

Description



WHAT YOU DO AT AMD CHANGES EVERYTHING 

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.  Together, we advance your career.  



THE ROLE: 

We are looking for a practical and experienced Staff Product Development Engineer (Data and AI Scientist) with a strong background in end-to-end development and deployment of AI and machine learning solutions for the semiconductor industry. 

 

THE PERSON: 

The ideal candidate should be comfortable working with large-scale datasets and designing algorithmic and scalable solutions. The candidate should also have excellent interpersonal skills for collaborating with engineering and business teams to deliver impactful outcomes.

 

KEY RESPONSIBILITIES: 

  • Design, develop, and deploy end-to-end machine learning pipelines—from data ingestion to model serving
  • Work with large, complex data sets to extract insights and build predictive or decision-support models
  • Implement scalable solutions that integrate with enterprise data and software systems
  • Ensure reliability, maintainability, and performance of deployed models in production environments
  • Collaborate with cross-functional teams to translate real-world challenges into effective data-driven solutions
  • Contribute to internal tooling and frameworks that accelerate AI/ML delivery

 

PREFERRED EXPERIENCE: 

  • Background in the semiconductor or electronics manufacturing domain
  • 7+ years of hands-on experience in deploying machine learning models and systems in production
  • Strong programming skills in Python, with experience in machine learning and/or deep learning libraries such as pandas, numpy, scikit-learn, PyTorch, or TensorFlow
  • Proven experience working with large-scale data processing, including distributed data environments (e.g., SQL, Spark, or cloud-native solutions)
  • Solid understanding of software engineering practices—version control, CI/CD, unit testing, containerization, and system monitoring, by using tools like GitHub, Bitbucket, etc.
  • Contributions to open-source projects or public AI/ML work (e.g., GitHub, blogs, academic publications)
  • Experience with platforms or tools like Snowflake, Databricks, MLflow, Airflow, graph database, LLM and agentic AI framework (e.g., LangChain, etc.).
  • Familiarity with one or both of the following:
    • Large Language Models (LLMs)-based agentic workflow implementations
    • Graph-based analytics or knowledge-driven modeling

 

ACADEMIC CREDENTIALS: 

  • Master's in Computer Engineering, Computer Science, Data Science, or a related technical field

LOCATION:

Singapore

 

#LI-HR1



Benefits offered are described:  AMD benefits at a glance.

 

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.


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