Product Development Engineer - AI & Analytics

ADVANCE YOUR CAREER. ADVANCE THE WORLD. 

At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. 

 

Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.

 

KEY RESPONSIBILITIES: 

• Design and develop software tools, automation frameworks, and data-driven solutions to improve Product Engineering productivity and execution efficiency. 
• Develop and maintain data pipelines, data models, analytics workflows, and data-quality checks that support engineering operations and decision-making. 
• Analyze engineering and manufacturing data to identify trends, anomalies, risks, bottlenecks, yield opportunities, and improvement actions. 
• Build dashboards, notebooks, reports, and visualizations for KPI tracking, engineering analytics, and management reporting. 
• Develop intelligent applications using machine learning, generative AI, prompt engineering, natural-language processing, anomaly detection, or LLM-based approaches where appropriate. 
• Integrate applications with enterprise and engineering systems through REST APIs to improve data accessibility, traceability, task management, and knowledge sharing. 
• Develop scalable solutions for issue tracking, workflow management, operational reporting, and engineering knowledge retention. 
• Build or support lightweight web applications and user interfaces for analytics, automation, or AI-enabled engineering workflows. 
• Define validation, evaluation, logging, and monitoring approaches to ensure outputs are accurate, traceable, useful, and suitable for engineering use. 
• Collaborate with stakeholders to gather requirements, define architectures, test solutions, support deployment, and drive user adoption. 
• Document designs, implementation steps, test results, user guides, limitations, risk controls, and best practices for maintainability and knowledge transfer. 

 

PREFERRED EXPERIENCES:

• Experience in Product Engineering, Software Engineering, Data Engineering, Analytics, Test Engineering, or a related technical discipline. 
• Python and programming - Strong Python skills for data processing, automation, analytics, report generation, engineering-log analysis, or AI application development. Experience with C or another language is an advantage. 
• Data analysis and SQL - Strong SQL fundamentals and experience extracting, transforming, cleaning, validating, modeling, and analyzing engineering or manufacturing data. 
• AI and machine learning - Practical knowledge of machine learning, generative AI, prompt engineering, NLP, anomaly detection, predictive analytics, or LLM applications. 
• Data visualization - Experience with Tableau, Power BI, matplotlib, Plotly, or equivalent tools for dashboards, yield/KPI tracking, analytics, and management reporting. 
• Web application development - Exposure to React, Vue, Flask, FastAPI, Django, or similar frameworks for building lightweight interfaces and applications is desirable. 
• API and system integration - Experience using REST APIs to connect applications with Jira, Confluence, Teams, SharePoint, Snowflake, Microsoft 365, AI services, or other enterprise platforms. 
• Agentic AI frameworks - Exposure to one or more agent or tool-calling frameworks or SDKs such as LangChain, LangGraph, OpenAI SDK, Semantic Kernel, CrewAI, AutoGen, or MCP is an advantage. 
• Cloud and data platforms - Exposure to Snowflake, Azure, AWS, Databricks, or similar enterprise and cloud data environments. 
• Linux and deployment - Familiarity with Linux, virtual machines, application hosting, deployment, and runtime troubleshooting is desirable. 
• DevOps and infrastructure - Experience with Git and exposure to CI/CD, Docker, Kubernetes, Terraform, logging, or monitoring is beneficial. 
• Engineering domain - Understanding of semiconductor manufacturing, Product Engineering, silicon test, diagnostics, yield analysis, reliability, BISR/MBIST, wafer-map analysis, or product bring-up is highly desirable. 
• Collaboration tools - Working familiarity with Jira, Confluence, Microsoft Teams, SharePoint, Outlook, Copilot, Excel, PowerPoint, and Word is advantageous. 
• Professional capabilities - Structured problem solving, attention to detail, proactive communication, clear technical documentation, strong learning agility, ownership, initiative, and ability to drive work from idea to implementation. 

 

ACADEMIC CREDENTIALS: 

• Bachelor’s or Master’s in electrical engineering, computer engineering, or comparable disciplines 

 

LOCATION:

Singapore

 

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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.

 

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD’s “Responsible AI Policy” is available here.

 

This posting is for an existing vacancy.