Product Engineer (Advance Data Analytics) - High Bandwidth Memory (HBM) Product Engineering

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD.; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

A leading semiconductor company in Singapore is looking for a key team member for their Advanced Data Analytics team. This role involves developing initiatives to improve yield and quality through advanced analytics and AI. Responsibilities include algorithm development, collaboration with cross-functional teams, and promoting innovation to maintain a competitive edge. A Bachelor’s or Master’s in relevant fields is required, along with familiarity with machine learning and tools like Power BI and Tableau.

Qualifications

• Familiarity with machine learning models in Python is a plus.
• Knowledge of regression and classification in Python would be advantageous.
• Required to work onsite in Singapore with international travel to Taiwan.

Responsibilities

• Utilize statistical tools and AI for engineering data analysis.
• Lead initiatives enhancing yield and quality improvement.
• Develop algorithms for quality enhancement and efficiency.
• Collaborate with various teams for successful product shipping.
• Promote innovation for technical advantage.
• Collaborate on AI/ML models to enhance KPIs.

Skills

Machine Learning

Data Analysis

Cross-Functional Collaboration

Statistical Tools

Education

Bachelor Degree/Master in Electrical and Electronics Engineering

Mechanical Engineering

Related Engineering field

Computer Science

Tools

Power BI

Tableau

Job description

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

As a key team member within the HIG HBM Product Engineering Advanced Data Analytics team, you will be spearhead and develop a high-performing team to drive initiatives that significantly enhance yield and quality through advanced data analysis, machine learning, and AI. Your responsibilities will include developing cutting-edge algorithms, creating robust product disposition solutions, and establishing a proactive deviation alert system for yield and quality, enhancing data infrastructure, mentor team members, and fostering innovation to maintain a competitive edge. You will also collaborate with cross-functional teams within and outside of HBM to achieve both strategic and tactical objectives, continually maximizing the effectiveness of the HIG HBM PE organization, focusing on critical KPIs such as quality, cost, cycle time, and scale.

Key Responsibilities

• Data Analysis for Yield Improvement and Reliability: Utilize in-house statistical tools, machine learning, and AI for engineering data analysis to enhance yields and reliability, integrating these improvements within the Dispo workflow.

• Cumulative Yield Ownership: Be a key member of cross-functional teams, to lead impactful initiatives that significantly enhance overall yield and quality improvement, driving substantial benefits for the organization.

• Models/Algorithm Development: Develop state-of-the-art algorithms, including Machine Learning and Deep Learning models, to advance data mining and pattern recognition for quality enhancement, yield improvement, wafer/die level screening and efficiency enhancement.

• Cross-Functional Collaboration: Work closely with various cross-functional teams, including Fab, HBM Technology Development, HBM Design, System Development, and Quality/Reliability teams, to ensure the holistic development and successful shipping of end products.

• Promotion of Innovation: Promote innovation and drive changes that provide a technical advantage over competitors, maintaining the company's competitive edge in the market.

• AI/ML Advocate: Collaborate with cross-functional teams to develop, deploy, and validate AI/ML models aimed at enhancing key performance indicators (KPIs) such as Quality, Cost, Cycle Time, and Scale.

Requirements

• A Bachelor Degree/Master in Electrical and Electronics Engineering , Mechanical Engineering, Related Engineering field, Computer Science.

• Familiarity with machine learning (regression and classification models in Python) is a plus.

• Knowledge of machine learning, especially regression and classification in Python, would be advantageous.

• Experience with BI tools like Power BI and Tableau

• Required to work onsite in Singapore with international travel to Taiwan.