Our vision is to transform how the world uses information to enrich life for all.
Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
As a Data Scientist at Micron, you will have the outstanding opportunity to apply innovative techniques and theories from fields like mathematics, statistics, semiconductor physics, materials science, and information technology. Your work will reveal patterns in data that create predictive models, actionable insights, and transformative solutions.
You will collaborate with experienced Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify critical questions and issues for data analysis projects. Your role will involve developing software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple sources. This position offers significant opportunities for exploratory and novel solution development activities, encouraging innovation and creativity.
Key Responsibilities
- Build and implement computer vision systems for object detection, image segmentation, anomaly detection, and automated inspection, using RGB-D cameras and vision inspection systems for volume/density measurement and component verification.
- Develop and deploy deep learning models (CNNs, LSTM, transformer-based architectures) for tasks such as image classification, time-series anomaly detection, and multimodal sentiment analysis, using frameworks like TensorFlow, PyTorch, and Keras.
- Employ advanced AI methods, such as few-shot learning, generative AI, and multimodal fusion (text, image, time-series), to address manufacturing and environmental monitoring challenges.
- Extract, cleanse, and analyze large-scale datasets from SQL databases, cloud platforms (AWS, GCP), and sensor networks, applying rigorous outlier detection and missing data handling methods.
- Guide cross-functional cooperation among engineering, operations, and quality departments, applying experience in project management, technical writing, and training/mentoring engineers in data science tools (Python, Spotfire, Power Automate).
- Coordinate production deployment activities using MLOps guidelines (MLflow, Apache Airflow), including model monitoring, data drift detection, versioning, and automated testing.
- Contribute to research and innovation through published patents, peer-reviewed papers, or presentations at top-tier conferences such as IJCNN, CVPR, and NeurIPS. Show the ability to translate research into practical solutions.
- Communicate technical concepts and project outcomes effectively to both technical and non-technical collaborators.
- 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.
Required Qualifications
- Possession of a Master’s degree in Computer Science, Data Science, or AI, or relevant equivalent experience.
- Two or more years of direct experience building and rolling out scalable AI applications in the manufacturing, semiconductor, or electronics industries.
Or
- Bachelor’s degree or equivalent experience in Computer Science, Data Science, or AI.
- Minimum 3 years of direct experience building and implementing scalable AI applications in manufacturing, semiconductor, or electronics industries.
Required Technical Experience
- Computer Vision: At least 2 years of experience crafting and implementing computer vision models for industrial uses. This includes object detection, image segmentation, and automated inspection with OpenCV, YOLO, and RGB-D cameras.
- Deep Learning & AI: Minimum of 2 years working with deep learning frameworks (TensorFlow, PyTorch, Keras), encompassing CNNs, LSTM, transformer models, and generative AI.
- Multimodal Analysis: Demonstrated skill in handling multimodal datasets (text, image, time-series), encompassing sentiment analysis and combining various data types.
- Programming & Data Engineering: Proficient in Python programming, with a minimum of 2 years of experience in SQL, Java, C++, and cloud environments (AWS, GCP); knowledge of distributed computing systems (Spark, Hadoop).
- MLOps & Deployment: Familiarity with MLflow, Apache Airflow, Docker, and Git for reliable model deployment and monitoring in live environments.
- Visualization & Communication: A minimum of 2 years working with visualization tools (Dash, Plotly, Spotfire, PowerBI) and producing technical writing for documentation and training.
- Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes.
Required Soft Skills
- Demonstrated analytical and problem-solving skills, with a target="_blank">hrsupport_sg@micron.com
Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.
Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.
AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.
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