MLOps Engineer

In this role you will own the AI-driven infrastructure and delivery pipelines that enable reliable, scalable ML-powered products on a cloud-native SaaS platform. You will contribute to architecture decisions and collaborate across ML, data, and product teams to deliver end-to-end features with a focus on performance, monitoring, and security. The work supports AECOM’s mission to transform infrastructure and reduce waste through data-driven solutions. You will operate in a lean, startup-like environment backed by a global engineering firm, delivering measurable real-world impact.

• medical, dental, vision benefits
• life and AD&D benefits
• disability benefits
• paid time off
• flexible work options
• retirement savings plan

• Build and maintain robust ML pipelines for training, deployment, and monitoring
• Develop backend systems and APIs integrating AI into the SaaS platform
• Own ML performance, monitoring, availability, and security
• Collaborate with ML engineers, data engineers, and product teams to deliver features end-to-end
• Contribute to architecture decisions for scalable, cloud-native ML infrastructure
• Stay up to date with MLOps practices and bring improvements to the workflow

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience)
• Solid programming skills in Python with web libraries (FastAPI, Flask, or Django)
• Hands-on experience with ML model deployment and monitoring in production
• Knowledge of containerization (Docker)
• Experience with CI/CD pipelines and cloud environments (Azure)
• Strong communication skills and a collaborative mindset

• collaborative mindset
• strong communication
• ownership and accountability
• Python programming
• FastAPI/Flask/Django web frameworks
• ML model deployment and monitoring