Senior ML Engineer: Defect Detection for 24/7 Manufacturing

Samsung Electronics; Taylor (TX); On-site; USD 106,000 - 145,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) matching with immediate vesting

Onsite cafe and workout facilities

Paid maternity and paternity leave

PTO and holidays

Job summary

Samsung Austin Semiconductor is seeking a Senior Machine Learning Engineer to lead defect-detection ML initiatives in a high-throughput manufacturing setting. You will own the ML lifecycle from modeling to deployment, partnering with domain experts and guiding a small team of engineers.

You will drive scalable vision models, optimize pipelines, and mentor others while ensuring reliability in a 24/7 environment. A strong track record in production ML and semiconductor contexts is highly valued.

Qualifications

• BS or MS in Software Engineering, Computer Science, Data Science, Mathematics or related STEM/Engineering degree.
• 5+ years relevant experience.
• Semiconductor industry highly preferred.
• Mastery of TensorFlow 2.x and PyTorch with production deployment.
• Proficiency with Ubuntu/Linux environments and hardware-aware optimization.
• Strong communication and execution history across projects.

Responsibilities

• Architect Advanced ML Solutions for defect detection and classification with high accuracy and throughput.
• Drive Domain Alignment translating defect characteristics into modeling proposals.
• Innovate via Research by adopting emerging AI architectures for production.
• Optimize the ML Pipeline with feature engineering and hyperparameter tuning.
• Ensure Operational Scalability for 24/7 production environments.
• Mentor & Lead junior engineers and enforce code quality standards.

Skills

TensorFlow 2.x

PyTorch

CNNs

Object Detection

Linux

Model deployment

Education

Bachelor's or Master in STEM

Tools

TensorFlow 2.x

PyTorch

Job description

Samsung Austin Semiconductor is seeking a Senior Machine Learning Engineer to lead defect-detection ML initiatives in a high-throughput manufacturing setting. You will own the ML lifecycle from modeling to deployment, partnering with domain experts and guiding a small team of engineers.

You will drive scalable vision models, optimize pipelines, and mentor others while ensuring reliability in a 24/7 environment. A strong track record in production ML and semiconductor contexts is highly valued.