Senior MLOps Engineer

Role Overview

Guild is seeking a Senior MLOps Engineer to help establish and scale its ML/AI platform. You will design and implement infrastructure and tooling that enables teams to efficiently develop, deploy, and iterate on machine learning models and AI agents.

Responsibilities

• Design, implement, and maintain platforms for deployment, management, and monitoring of ML models and AI agents
• Develop and optimize CI/CD pipelines tailored to AI and machine learning workflows
• Collaborate with data scientists, software engineers, and product teams to streamline ML productionization
• Ensure infrastructure is scalable, secure, and aligned with reliability and observability best practices
• Provide technical leadership for model governance, versioning, testing, and validation
• Continuously improve platform performance, efficiency, and usability to accelerate development cycles
• Mentor team members on MLOps standards, practices, and emerging technologies

What You Bring

• 5–7 years of experience in MLOps, DevOps, software engineering, or related fields
• Strong experience building and maintaining scalable ML infrastructure and pipelines
• Expertise with cloud platforms (AWS, Azure, or GCP), especially managed AI/ML services
• Proficiency with Docker and Kubernetes (containerization and orchestration)
• Experience with MCP (Model Context Protocol); Databricks MCP or AWS MCP experience is a plus
• Experience with model deployment frameworks/serving infrastructure, e.g. TensorFlow Serving, TorchServe, FastAPI
• Infrastructure-as-code: Terraform; CI/CD automation with GitHub Actions or Jenkins
• ML lifecycle management and tooling such as MLflow, Kubeflow, and Weights & Biases
• Strong coding skills, especially Python, plus familiarity with software engineering best practices
• Knowledge of monitoring, logging, and alerting systems for ML models in production

Nice to Have / Plus

• Specific experience with Databricks MCP or AWS MCP