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Open nowPosted today

Senior Engineer, STPG PE NAND

MyCareersFuture95,505 open roles

Pay
SGD 6,000 – SGD 10,000 a month
Where
North, Singapore
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Your applicationOpen nowSenior Engineer, STPG PE NANDMyCareersFuture · North, Singapore

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10.1% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 8 days.

Share of postings closed within
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  2. 4.0%3 days
  3. 10.1%7 days
  4. 15.8%14 days
  5. 34.0%30 days
This job: posted today

MyCareersFuture median: 8 days open

The posting

As a NAND Reliability Product Engineer, you will be responsible for defining, assessing, and safeguarding the intrinsic and extrinsic reliability of Micron's NAND Flash products through advanced analytics, large-scale data infrastructure, AI, and engineering innovation. Your responsibilities will include developing scalable data and AI solutions that enable faster engineering decisions, improving product quality, and strengthening reliability risk assessment. Working at the intersection of semiconductor technology, reliability engineering, cloud computing, and AI/ML, you will collaborate closely with other teams like AI, IT, and Quality teams to drive data-driven reliability strategies and prevent customer escapes.

This role offers deep technical ownership at the intersection of reliability methodologies, analytics platforms, and AI-enabled engineering workflows, with strong visibility across development and manufacturing organizations.

Main Responsibilities:

  • Drive development and enhancement of cloud-based data platforms that support reliability monitoring, engineering analysis, and product disposition workflows.
  • Design, develop, and maintain scalable ETL pipelines for ingesting, validating, transforming, and managing large-scale engineering and manufacturing data from multiple sources.
  • Collaborate with IT and data platform teams to establish reliable, automated, and sustainable data pipelines.
  • Apply technologies such as Python, SQL, BigQuery, PySpark, and cloud-native services to process large-scale datasets efficiently, perform deep analysis, generate visualizations, and deliver actionable engineering insights.
  • Partner with domain experts and cross-functional teams to translate complex engineering problems into scalable AI/ML and analytics solutions.
  • Develop, evaluate, and deploy AI/ML solutions to improve engineering decision-making, failure analysis, anomaly detection, and reliability assessments.
  • Implement robust data processing techniques such as data cleansing, outlier detection, and missing data handling using distributed or large-scale frameworks (e.g., PySpark, BigQuery).
  • Support deployment, monitoring, and operationalization of AI/ML solutions in cloud and enterprise environments.
  • Identify and drive high-impact opportunities where GenAI, machine learning, and analytics can improve engineering productivity and business outcomes.
  • Integrates AI-assisted tools and data-driven insights to improve productivity, quality, and operational effectiveness in daily work.
  • Promote adoption of AI-enabled solutions and contribute to a culture of continuous learning, innovation, and operational excellence.
  • Support customer inquiries and provide technical insights related to product reliability.
  • Communicate technical findings, recommendations, and model outcomes clearly to both technical and non-technical stakeholders.

AI Responsibilities:

  • Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements
  • Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.

Minimum Required Qualifications/Experience

  • Bachelor’s degree with > 5 years or Master’s degree with > 3 years in Electrical Engineering, Computer Science, Data Science, Statistics, Artificial Intelligence, or related discipline.
  • Strong understanding of data analytics, AI/ML, or related technical fields.
  • Knowledge of semiconductor reliability fundamentals, NAND technology, reliability engineering, and electrical failure analysis methodologies.
  • Strong programming proficiency in Python and SQL.
  • Understanding data engineering concepts, including data cleansing, outlier treatment, missing data handling, and scalable data processing.
  • Strong analytical, problem-solving, communication, and technical presentation skills.
  • Demonstrated sense of ownership, accountability, and ability to work effectively in cross-functional environments.

Highly Desirable/Preferred skills or experience

  • Strong technical foundation in data analytics and visualization, including tools and libraries such as pandas, scikit-learn, matplotlib, plotly, or similar ecosystems.
  • Hands-on experience developing and deploying AI/ML systems involving LLMs, including RAG, agentic workflows, and frameworks such as PyTorch or TensorFlow.
  • Familiarity with modern AI coding tools / agentic coding harnesses, such as Claude Code, Roo Code, Cursor, Cline, Windsurf, Gemini CLI, or similar tools.
  • Cloud experience with GCP, AWS, or Azure, including deploying ML pipelines in production.
  • Experience analyzing large, complex, and heterogeneous datasets from multiple systems and applying sound techniques for data cleansing, outlier handling, and missing data treatment.
  • Team player and self driver.

Embody Micron’s core values:

  • People – Respect, develop, and empower others
  • Innovation – Drive continuous improvement and breakthrough thinking
  • Tenacity – Show grit and determination
  • Collaboration – Build trust and foster teamwork
  • Customer Focus – Deliver excellence and value
  • Speed – Act with purpose and set the pace
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