Machine Learning Engineer II
Corp-Main - Diamond Bar, CA, United States
USD 100K-145K Mid-level Full Time
Tasks
- Build and maintain scalable training and inference pipelines
- Build supervised and unsupervised machine learning models
- Deploy low latency models to cloud and edge endpoints
- Design predictive and prescriptive maintenance systems
- Detect anomalies and predict remaining useful life
- Develop agentic AI decision workflows
- Develop data preprocessing pipelines for industrial sensor data
- Establish MLOps pipelines to monitor drift and retrain models
- Integrate predictions with dashboards and CMMS workflows
- Optimize model training throughput and distributed compute
Perks/Benefits
- N/A
Skills/Tech-stack
Agent systems | Agentic AI | Anomaly Detection | Autoencoders | Azure | Azure Machine Learning | C plus plus | CI/CD | Databricks | Docker | Dynamic Time Warping | InfluxDB | Isolation Forest | Kubeflow | Kubernetes | LLMOps | LSTM | Language Processing | MLOps | MLflow | Machine Learning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | NumPy | One-Class SVM | PCA | Pandas | Predictive Maintenance | Prescriptive Maintenance | PySpark | PyTorch | Python | R | Random Forests | Remaining useful life | Retrieval-Augmented Generation | SQL | SciPy | Scikit-learn | Series forecasting | Supervised Learning | TensorFlow | Time Series | Time Series Forecasting | TimescaleDB | Unsupervised Learning | XGBoost
Education
Regions
Countries
States
Cities
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