Senior Machine Learning Engineer

In this AI Engineering role at AECOM, you design and scale ML models that impact real-world infrastructure. You’ll own the modelling lifecycle, from problem framing to deployment, and work closely with MLOps and product teams to embed AI into our SaaS platform. You will tackle complex problems, drive robust experimentation, and mentor others while delivering measurable outcomes for engineering projects.

• medical insurance
• dental insurance
• vision insurance
• life/AD&D benefits
• disability benefits
• paid time off

• Lead design and development of advanced ML models with measurable impact for infrastructure applications
• Own end-to-end modelling lifecycle: problem formulation, feature strategy, experimentation, deployment, iteration
• Transform complex, ambiguous problems into scalable ML solutions
• Create robust experimentation frameworks and evaluation methods for real-world model performance
• Diagnose failure modes and balance performance trade-offs; continuously improve models post-deployment
• Collaborate with MLOps and software engineering to productionize models while ensuring quality
• Partner with product managers, engineers, and domain experts to embed AI in our SaaS platform
• Provide technical leadership, mentoring, and setting modelling standards and direction

• Proven experience developing and deploying ML models in production settings
• Strong expertise in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Depth in model design, optimization, and evaluation beyond standard approaches
• Strong intuition for model failure modes, generalization, and real-world performance trade-offs
• Experience owning ML initiatives end-to-end from problem definition to deployment
• Clear communicator able to explain modelling decisions to diverse stakeholders

• Strong communication and collaboration
• Mentoring and technical leadership
• Ownership and accountability
• Python
• PyTorch
• TensorFlow