TriNet is seeking a Staff MLOps Engineer to lead the design and operation of our production ML platform supporting HR, payroll, and benefits solutions for thousands of SMB clients. You will architect scalable, secure ML infrastructure; build CI/CD pipelines for models and data; and implement monitoring for performance, drift, and reliability. Partnering with data science, engineering, and product, you'll standardize MLOps best practices, mentor engineers, and drive automation that accelerates experimentation while ensuring compliance in a fast-paced, collaborative environment.
Responsibilities
- Design and own end-to-end MLOps architecture for scalable, secure ML deployments.
- Build and maintain CI/CD pipelines for ML models, data pipelines, and services.
- Implement monitoring, logging, and alerting for model performance, data drift, and reliability.
- Collaborate with data scientists and engineers to productionize models and automate workflows.
- Optimize cloud infrastructure, containers, and orchestration for cost, performance, and resilience.
- Establish best practices, standards, and documentation for MLOps across teams.
- Ensure compliance, security, and governance for ML data and services.
- Mentor engineers and influence technical direction for ML platforms.
Required Skills
- MLOps
- Machine learning deployment
- CI/CD for MLCloud platforms (AWS/Azure/GCP)
- Containerization (Docker/Kubernetes)
- Model monitoring & observability
- Data pipelines (ETL/ELT)
- Python
- Infrastructure as Code (Terraform/Cloud
- Formation)
- ML experiment tracking (MLflow/Kubeflow)