Senior MLOps Engineer

Overview

In this senior role within AECOM’s AI Engineering team, you own the production ML infrastructure and delivery workflows that move models from experiment to reliable production. You will influence technical direction, architecture, and system stability in a lean, high-ownership environment backed by a leading engineering firm. You partner with ML engineers, data engineers, and product teams to deliver scalable AI products that improve infrastructure design and sustainability. This is your chance to shape real-world impact at scale within a mission-driven company.

Pay / Benefits

• medical, dental, vision benefits
• life and disability benefits
• paid time off and leaves
• flexible work options
• retirement savings plan
• employee stock purchase plan

Responsibilities

• Own and evolve production ML infrastructure for training, deployment, serving, and monitoring
• Build and improve CI/CD, automation, and model delivery workflows across the engineering team
• Develop Python services, APIs, and platform tooling for production ML workloads
• Ensure reliability, observability, performance, availability, and security of production ML systems
• Troubleshoot complex production issues across software, infrastructure, and ML workflows
• Drive architecture decisions and collaborate with ML engineers, data engineers, and product teams to deliver scalable AI products

Key requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience)
• Experience deploying, operating, monitoring, and supporting ML systems in production
• Experience building and owning ML pipelines, model deployment, serving, monitoring, or lifecycle infrastructure
• Strong Python skills, plus experience with web frameworks (FastAPI, Flask, or Django)
• Hands-on experience with Docker, CI/CD pipelines, and Azure cloud
• Ability to make architecture decisions and troubleshoot complex production systems for reliability, scalability, and performance
• Ability to operate independently, take end-to-end ownership, and provide technical leadership in a collaborative team
• Strong communication skills and a collaborative mindset

• collaborative mindset
• strong communication
• independence and ownership
• Python
• FastAPI, Flask, or Django
• Docker

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