MLOPS Engineer

Location: Concord, CA (100% Onsite)
Hire Type: Contract
Employment Eligibility: and USC

Role Summary

Seeking a Senior MLOps Engineer to build, deploy, and operate production-grade ML systems. This role focuses on automating the ML lifecycle, enabling scalable cloud deployments, and ensuring model reliability, monitoring, and governance in an enterprise environment.

Key Responsibilities

• Build and maintain end-to-end ML pipelines using MLflow, Kubeflow, or Vertex AI

• Automate model training, testing, deployment, monitoring, and retraining

• Implement CI/CD workflows for model versioning and lifecycle management

• Deploy ML workloads on Google Cloud Platform, AWS, or Azure using Docker and Kubernetes

• Monitor model performance, drift, and compliance with model governance (MRM, explainability)

• Support low-latency inference APIs for real-time and batch scoring

• Leverage AutoML tools (Vertex AI AutoML, H2O Driverless AI) for rapid model delivery

Required Qualifications

• 10+ years in Software Engineering and 3+ years in MLOps / ML Operations

• Strong hands-on experience with Java, Python, SQL

• Experience with ML frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch)

• Hands-on delivery of 3–4 production ML projects

• Experience with Docker, Kubernetes, CI/CD pipelines

• Familiarity with Airflow, Spark, and ML Ops frameworks

• Strong communication and stakeholder management skills