MLOPS Engineer

Job Description

Job Description

Location : Concord, CA ( 100% Onsite )

Hire Type : Contract

Employment Eligibility : GC 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