Senior Machine Learning Engineer

In AECOM’s AI for 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. 

Our AI for Engineering team combines the speed, ownership, and technical ambition of a startup with the scale, resources, and domain expertise of one of the world’s leading engineering firms.

You’ll work on challenging applied machine learning problems spanning optimization, simulation, and real-world engineering systems, building models that move beyond experimentation and into products used to solve tangible infrastructure challenges. These are often complex, ambiguous problems where the solution is not already defined.

What You’ll Do 

• Lead the design and development of advanced machine learning models that deliver measurable impact across engineering and infrastructure applications.
• Own the end-to-end modelling lifecycle—from problem formulation and feature strategy through experimentation, validation, deployment, and iteration.
• Tackle complex, ambiguous problems and translate them into scalable ML solutions.
• Design robust experimentation frameworks and evaluation methodologies that measure real-world model performance.
• Diagnose model failure modes, evaluate performance trade-offs, and continuously improve models after deployment.
• Collaborate closely with MLOps and software engineering teams to productionize models while maintaining a strong focus on modelling quality and performance.
• Partner with product managers, engineers, and domain experts to embed AI capabilities into our SaaS platform.
• Provide technical leadership across ML initiatives, mentoring other engineers and helping shape modelling approaches, experimentation standards, and technical direction.