Machine Learning Engineer/MLOps

About the role

Build, deploy, and manage production-ready machine learning systems.

Tasks

• Design and implement production-grade machine learning systems.
• Build automated pipelines for data preparation, model training, testing, and deployment.
• Deploy models for batch and real-time inference.
• Manage experiment tracking, model versioning, and reproducible workflows.
• Implement CI/CD pipelines for machine learning applications.
• Monitor model performance, data quality, drift, latency, and service health.
• Collaborate with data scientists and data engineers to operationalize ML models.

Requirements

• 9+ Years
• H-4 EAD | GC EAD | Green Card (GC) | F-1 OPT | STEM OPT
• Candidates must meet the position's applicable work authorization and employment requirements.
• Strong proficiency in Python and production software engineering.
• Experience deploying machine learning models in production.
• Hands-on MLOps experience with experiment tracking and model registries.
• Machine Learning Engineering | MLOps | Python | Model Deployment | ML Pipelines | CI/CD for ML | Model Monitoring | Docker/Kubernetes | MLflow/Kubeflow | SQL/Data Pipelines Cloud ML Platforms | Experiment Tracking

Schedule

• Hybrid
• W2 Contract

Location

• Austin, TX