Samsung Austin Semiconductor is seeking a Machine Learning Engineer (onsite in Taylor, TX) to build and maintain production ML pipelines for anomaly detection and root cause analysis.
Responsibilities
- Develop PySpark workflows to ingest, clean, and transform high-volume manufacturing data into structured datasets for training and inference.
- Improve performance of Spark jobs by tuning partition strategies , managing executor memory , reducing shuffle operations, and addressing skewed joins to lower runtime and cluster resource usage.
- Create and maintain end-to-end ML pipelines that automate feature calculation, model training, validation, and deployment with runs that are reproducible and auditable .
- Build and tune machine learning models for anomaly detection and root cause analysis .
- Manage model lifecycle in production by tracking model versions , storing artifacts securely, triggering automated retraining , and performing rollback procedures when performance degrades.
- Monitor pipeline execution time, data quality checks , and model metrics including accuracy, drift, and throughput ; implement alerting rules to catch failures or degradation early.
Requirements
- Bachelor’s degree or higher in Computer Science, Software Engineering, Data Science, or a related quantitative field.
- 3-5+ years of professional experience building and maintaining machine learning systems.
- Strong proficiency in PySpark and distributed data processing , including experience optimizing jobs for speed and memory.
- Hands-on experience with Python ML libraries including one or more of: scikit-learn, TensorFlow, PyTorch, XGBoost for training and evaluation.
- Practical knowledge of MLOps , including pipeline orchestration, model versioning, experiment tracking, and deployment.
- Experience setting up monitoring and alerting for data pipelines and deployed models.
Technologies
- PySpark
- Spark
- Python
- scikit-learn
- TensorFlow
- PyTorch
- XGBoost
Benefits
- Medical, dental, and vision insurance
- Life insurance and 401(k) matching with immediate vesting
- Onsite café(s) and workout facilities
- Paid maternity and paternity leave
- Paid time off (PTO) + 2 personal holidays and 10 regular holidays
- Wellness incentives and MORE
- Eligible full-time employees (salaried or hourly) may receive MBO bonuses based on company, division, and individual performance
Preferred
- Experience setting up model registries, automated retraining triggers, and rollback procedures to support reliable production models.
- Experience writing automated tests and validation checks for data pipelines and model outputs to catch errors before deployment.
- Familiarity with on-prem or private cloud infrastructure, including cluster management and secure artifact storage.
Compensation and Work Model
- Base pay range: $90,000 - $174,500 per year
- Work model: Full-time, on-site at Samsung Austin Semiconductor
U.S. Export Control Compliance
- This role may require access to information subject to U.S. export control laws; applicants must be authorized to access such information or eligible for government authorization.
Trade Secrets Notice
- By submitting an application, you agree not to disclose to Samsung, or encourage Samsung to use, any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.
Machine Learning Engineer in taylor at Unknown Company
This position is listed as full time and onsite.