ML Ops Engineer

Hi, 12+ Years of Exp Role: ML Ops Engineer Location : SF Bay Area ONLY (San Leandro Preferably) The Job: Note : Candidate with strong experience in understanding of Google/Azure and Spark/Python and MLOPs . Strong ML engineer with fair knowledge of Data science is fine. Key Responsibilities • Develop predictive models using structured/unstructured data across 10+ business lines, driving fraud reduction, operational efficiency, and customer insights. • Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment • Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI. • Automate model training, testing, deployment, and monitoring in cloud environments (e.g., GCP, AWS, Azure). • Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining. • Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability) • Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs Qualifications • Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch). • Experience with cloud platforms and containerization (Docker, Kubernetes). • Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks. • Solid understanding of software engineering principles and DevOps practices. • Ability to communicate complex technical concepts to non-technical stakeholders. Thanks & Regards.., Arun Prasath 704-412-4724 arun@reveilletechnologies.com