Senior MLE - MLOps, Python, GCP, VertexAI, GKE

The Senior MLOps Engineer will design, deploy, and manage machine learning pipelines within the Google Cloud Platform (GCP) environment. This role focuses on automating ML workflows, optimizing model deployment, ensuring system reliability, and implementing robust CI/CD pipelines. You will collaborate with architects and business stakeholders to build scalable, cost-efficient ML infrastructure that delivers business value.

Responsibilities

• Manage the deployment and maintenance of production ML models, ensuring seamless system integration.
• Monitor model performance using metrics such as accuracy, precision, recall, and F1 score, while mitigating drift, bias, or performance degradation.
• Troubleshoot issues, maintain technical documentation, and manage model versions for audit and rollback purposes.
• Analyze monitoring data to preemptively identify potential issues and report performance to stakeholders.
• Optimize data queries and pipelines while modernizing applications as needed.

Required Qualifications

• Bachelor’s degree in a quantitative field (Mathematics, Computer Science, Physics, Economics, Engineering, Statistics, etc.) or equivalent experience.
• Expertise in Python and SQL.
• Solid understanding of MLOps best practices for enterprise-level systems.
• Proficiency in ML concepts, including regression, clustering, and neural networks (Deep Learning, Transformers).
• Experience with GCP tools including BigQueryML, Vertex AI Pipelines (Kubeflow), Model Registry, and Cloud Monitoring.
• Strong communication skills and ability to create detailed technical documentation.

Bonus Qualifications:

• Experience with Azure MLOps and Cloud Billing.
• Familiarity with setting up or supporting NLP, Generative AI, or LLM applications.
• Experience working in an Agile environment.