ML Ops Engineer
Location: Concord, CA (Local candidates only – In-person interview required)
Experience Level: 10+ Years Software Engineering | 3+ Years MLOps/AI-ML
Role Overview
Seeking a senior-level ML Ops Engineer to join our Machine Learning AI team. In this role, you will be the backbone of our model lifecycle, driving the development, automation, and scaling of sophisticated machine learning solutions. You will bridge the gap between data science and production engineering to ensure our models are robust, explainable, and high-performing.
Key Responsibilities
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Pipeline Orchestration: Design, develop, and maintain end-to-end ML pipelines using industry-standard tools such as MLflow, Kubeflow, or Vertex AI.
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Governance & Observability: Monitor real-time model performance using observability tools. Ensure all deployments meet strict Model Risk Management (MRM) frameworks, focusing on documentation and explainability.
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Infrastructure & Deployment: Collaborate with DevOps teams to provision containerized environments (Docker/Kubernetes) and support high-throughput, low-latency API scoring.
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Low-Code/No-Code Innovation: Leverage AutoML (Vertex AI, H2O Driverless AI) to accelerate model development and automate documentation processes.
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