MLOps Engineer

Work with Us. Change the World. At AECOM, we're delivering a better world. Whether improving your commute, keeping the lights on, providing access to clean water, or transforming skylines, our work helps people and communities thrive. We are the world's trusted infrastructure consulting firm, partnering with clients to solve the world’s most complex challenges and build legacies for future generations.

In AECOM’s AI Engineering team your code will directly shape the physical world around us. We build AI-driven technology that revolutionises how infrastructure and buildings are designed and engineered; reducing waste, cutting CO₂, and making the built environment more efficient and sustainable. This is where software has measurable, real-world impact.

As part of our AI Engineering team, you will own the infrastructure and delivery pipelines that keep our AI-driven products reliable, scalable, and fast. This is a high-ownership role where your decisions directly affect developer velocity and production stability.

• Build and maintain robust ML pipelines for training, deployment, and monitoring
• Develop backend systems and APIs that integrate AI into our SaaS platform
• Take ownership of the 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 the latest in MLOps practices and tools, and bring improvements into the workflow

Must-Have Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience)
• Solid programming skills in Python (plus experience with web libraries like 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 (we use Azure)
• Strong communication skills and a collaborative mindset

Preferred Skills

• Experience with model versioning and experiment tracking (e.g. MLflow, Weights & Biases)
• Understanding of optimizing both CPU-bound and GPU-bound workloads
• Knowledge of monitoring and observability tools (e.g. Prometheus, Grafana, ELK stack)
• Background in optimization, reinforcement learning, or generative AI (a plus, not required)
• Identifying and resolving bottlenecks in distributed machine learning workloads (knowledge of low-level languages and CUDA library is a plus)

Our Hiring Process

• Take-home challenge: A hands-on task to assess your problem-solving and technical skills
• Combined technical and cultural interview (in-person)
• Whiteboard Interview: 1-hour with 2 of our engineers to discuss your solution to the take-home challenge
• Culture fit: 30-minute meeting with our leadership team

Why Join Us?

• Work on real-world problems where AI creates measurable impact.
• Be part of a team where your work matters, and your ideas become real.
• Collaborate with sharp, driven colleagues in a culture of trust, ownership, and high standards.
• Contribute to making the built environment smarter and more sustainable.

To support this commitment, all newly hired employees are required to attend an in-person Day 1 onboarding at an AECOM office location as a condition of employment.

AECOM is proud to offer comprehensive benefits to meet the diverse needs of our employees. Depending on your employment status, AECOM benefits may include medical, dental, vision, life, AD&D, disability benefits, paid time off, leaves of absences, voluntary benefits, perks, flexible work options, well-being resources, employee assistance program, business travel insurance, service recognition awards, retirement savings plan, and employee stock purchase plan.

AECOM is a Fortune 500 firm that had revenue of $16.1 billion in fiscal year 2025.

We are a Disability Confident Employer and will offer an interview to applicants who have a disability or long-term condition, who meet the minimum/essential criteria for the role.