Senior Machine Learning Engineer

As a highly skilled MLOps Engineer at UPS, you will design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). Your responsibilities will include automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. Your role will involve collaborating with technical teams and business stakeholders to develop cutting-edge machine learning systems that add value to the business. Responsibilities: - Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. - Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. - Troubleshooting and resolving problems, maintaining documentation, and managing model versions for audit and rollback. - Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. - Optimization of queries and pipelines. - Modernization of applications whenever required. Qualifications: - Expertise in programming languages like Python, SQL. - Solid understanding of best MLOps practices and concepts for deploying enterprise-level ML systems. - Understanding of Machine Learning concepts, models, and algorithms including traditional regression, clustering models, and neural networks (including deep learning, transformers, etc.). - Understanding of model evaluation metrics, model monitoring tools, and practices. - Experience with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. - Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. - Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. - Bachelor's Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: - Experience in Azure MLOPS. - Familiarity with Cloud Billing. - Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. - Experience working in an Agile environment, understanding of Lean Agile principles. UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.,