Data Scientist
Reads like a ML Engineer role: putting models into production.
Location not identified
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and implement computer vision systems for defect inspection and anomaly detection
Develop and deploy deep learning models such as CNNs, LSTMs and transformers
Apply generative AI and multimodal fusion to manufacturing and environmental monitoring problems
Extract, cleanse and analyze large datasets from SQL, GCP and image sources
Coordinate production model deployment with monitoring, drift detection and versioning
From the employer’s posting
Design and implement computer vision systems for object detection, image segmentation, anomaly detection, and automated inspection
Develop and deploy deep learning models (CNNs, LSTM, transformer-based architectures)
Apply advanced AI techniques including few-shot learning, generative AI, and multimodal fusion (text, image, time-series) to solve manufacturing and environmental monitoring challenges.
Extract, cleanse, and analyze large-scale datasets from SQL databases, cloud platform (GCP), and image data
Coordinate production deployment activities using MLOps best practices including model monitoring, data drift detection, versioning, and automated testing.
Education & alternatives
Required Qualifications * Bachelor’s degree in Computer Science, Data Science or AI. * Minimum 1-2 years of hands-on experience developing and deploying scalable AI applications in manufacturing, semiconductor, or electronics industries. * Required Technical Experience * Computer Vision: At least 1-2 years of working experience in designing and deploying computer vision models for industrial applications, including object detection, image segmentation, and automated inspection using OpenCV. * Deep Learning & AI: At least 1 year of working experience with deep learning frameworks (TensorFlow or PyTorch), including CNNs and generative AI. * Multimodal Analysis: Proven ability to work with multimodal datasets (image with text or time-series), including sentiment analysis or fusion of multiple data types. * Programming & Data Engineering: Strong Python programming skills; at least 1 year working experience with SQL; familiarity with distributed computing frameworks (Spark or Hadoop). *
Tools in this posting
- Python
- SQL
- GCP
- Hadoop
- Spark
- Keras
- PyTorch
- TensorFlow
Source — Tool mentions in context
* Bachelor’s degree in Computer Science, Data Science or AI. * Minimum 1-2 years of hands-on experience developing and deploying scalable AI applications in manufacturing, semiconductor, or electronics industries. * Required Technical Experience * Computer Vision: At least 1-2 years of working experience in designing and deploying computer vision models for industrial applications, including object detection, image segmentation, and automated inspection using OpenCV. * Deep Learning & AI: At least 1 year of working experience with deep learning frameworks (TensorFlow or PyTorch), including CNNs and generative AI. * Multimodal Analysis: Proven ability to work with multimodal datasets (image with text or time-series), including sentiment analysis or fusion of multiple data types. * Programming & Data Engineering: Strong Python programming skills; at least 1 year working experience with SQL; familiarity with distributed computing frameworks (Spark or Hadoop). * Required Soft Skills
Key Responsibilities * Design and implement computer vision systems for object detection, image segmentation, anomaly detection, and automated inspection, including experience with vision inspection systems for volume/density measurement and defect monitoring. * 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, leveraging frameworks like TensorFlow, PyTorch, and Keras. * Apply advanced AI techniques including few-shot learning, generative AI, and multimodal fusion (text, image, time-series) to solve manufacturing and environmental monitoring challenges. * Extract, cleanse, and analyze large-scale datasets from SQL databases, cloud platform (GCP), and image data, applying rigorous outlier detection and missing data handling. * Lead cross-functional collaboration with engineering, operations, and quality teams, including experience in project management, technical writing, and training/mentoring engineers in AI applications. * Coordinate production deployment activities using MLOps best practices including model monitoring, data drift detection, versioning, and automated testing. * Communicate technical concepts and project outcomes effectively to both technical and non-technical stakeholders. Required Qualifications
Posting record
Report an errorActively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 26, 2026 · 3 days ago
- Recorded sightings
- 13
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on careers.micron.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Location not supplied.
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.