ML Engineer: Spark Pipelines for Anomaly Detection

Samsung Electronics America; Temple (TX); On-site; USD 90,000 - 175,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) matching

Onsite café and fitness facilities

Paid family leave

Job summary

Samsung Austin Semiconductor is seeking a Machine Learning Engineer to build and maintain model pipelines for anomaly detection and root cause analysis. You will harness PySpark to process large-scale time-series data, prepare training datasets, and manage the full deployment lifecycle in production.

You will design robust ML pipelines, validate models, optimize Py Spark jobs, and collaborate with teams in a sprint-driven environment.

Qualifications

• 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, with experience optimizing jobs for speed and memory.

Responsibilities

• Build PySpark workflows that ingest, clean, and transform high-volume manufacturing data, converting raw signals into structured datasets ready for training and inference.
• Optimize Spark jobs by tuning partition strategies, managing executor memory, minimizing shuffle operations, and handling skewed joins to reduce runtime and cluster resource usage.
• Design and maintain end-to-end ML pipelines that automate feature calculation, model training, validation, and deployment, ensuring each run is reproducible and auditable.
• Implement and tune machine learning models for anomaly detection and root cause analysis.
• Manage the model lifecycle in production: track versions, store artifacts securely, trigger automated retraining, and execute rollback procedures when performance degrades.
• Monitor pipeline execution times, data quality checks, and model metrics (accuracy, drift, throughput), building alerting rules to catch failures or degradation early.

Skills

PySpark

Distributed processing

Python ML libraries

MLOps

Model deployment

Monitoring & alerting

Education

Bachelor’s degree or higher

Tools

scikit-learn

TensorFlow

PyTorch

XGBoost

Job description

Samsung Austin Semiconductor is seeking a Machine Learning Engineer to build and maintain model pipelines for anomaly detection and root cause analysis. You will harness PySpark to process large-scale time-series data, prepare training datasets, and manage the full deployment lifecycle in production.

You will design robust ML pipelines, validate models, optimize Py Spark jobs, and collaborate with teams in a sprint-driven environment.