ML Ops Engineer JR

Description

Job Summary: We are seeking an MLOps specialist freelancer to automate, deploy, monitor, and scale Machine Learning models in production environments. Key Highlights: 1. Flexibility in challenging and high-impact projects at uCloud. 2. Supporting the operationalization of Machine Learning models in production. 3. Continuous collaboration with Data Scientists and Data Engineers. **Description:** ---------------- We are looking for freelance MLOps specialists to join various challenging and high-impact projects at uCloud. We are building our own exclusive talent pool to connect with top professionals in the field. If you are passionate about GCP architecture and seek flexibility, apply now. Your goal will be to automate, deploy, monitor, and scale Machine Learning models in production environments, bridging the gap between development and operations. **Requirements:** --------------- Support the operationalization of Machine Learning models in production environments, contributing to automation, stability, and correct execution of pipelines under the guidance of more senior roles. * Support implementing training and inference pipelines. * Execute and validate model deployments in development and testing environments. * Assist with versioning of models, datasets, and ML artifacts. * Perform basic monitoring of model performance and availability metrics. * Identify and report incidents in pipelines and executions. * Continuously collaborate with Data Scientists and Data Engineers. * Document technical processes and ML Ops workflows. Stack: Basic knowledge of Vertex AI (GCP), intermediate Python, foundational MLOps concepts, CI/CD, Docker, and automation. Experience: 2 years of experience in Data, ML, or DevOps roles, with initial experience supporting ML deployments or pipelines.