Machine learning engineer

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.

• 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.

• Proven experience developing and deploying ML models in production settings
• Master’s or PhD in Engineering, Computer Science, Applied Mathematics, Data Science, Operations Research, or a related field
• Strong expertise in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Demonstrated depth in model design, optimization, and evaluation beyond standard off-the-shelf approaches
• Strong intuition for model failure modes, generalization, and real-world performance trade-offs
• Experience owning machine learning initiatives end-to-end, from problem definition through deployment and iteration.
• Proven ability to independently scope, execute, and deliver high-impact ML initiatives
• Clear communicator who can explain complex modelling decisions and trade-offs to diverse stakeholders
• Будет плюсом: Experience applying machine learning to engineering-heavy or physical-world domains such as mechanical engineering, construction, transportation, HVAC, energy systems, or robotics; Background in optimisation, simulation, scientific machine learning, physics-informed learning, or digital twins; Experience with time-series forecasting, computer vision, sensor data, or other complex engineering datasets; Track record of mentoring or technically leading ML initiatives

• 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.
• 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.
• 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.