At a Glance
- Tasks: Lead the design and development of AI/ML models that make a real-world impact.
- Company: Join AECOM, a global leader in infrastructure consulting.
- Benefits: Comprehensive benefits, flexible work options, and career growth opportunities.
- Other info: Collaborative culture with a focus on innovation and sustainability.
- Why this job: Work on groundbreaking projects that shape the future and improve communities.
- Qualifications: Experience in ML model development and strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
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.
What You’ll Do:
- Lead the design and development of advanced AI/ML models that deliver measurable impact in the engineering domain.
- Own the end-to-end modelling lifecycle — from problem formulation and feature strategy to validation and production handoff.
- Tackle complex, ambiguous problems and translate them into scalable ML solutions.
- Design robust experimentation frameworks and define evaluation methodologies that ensure real-world performance.
- Collaborate closely with MLOps to productionize models while focusing on modelling excellence and performance optimization.
- Partner with product managers, engineers, and domain experts to embed AI capabilities into our SaaS platform.
Qualifications:
Must-Have Qualifications:
- 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.
- 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.
Preferred Skills:
- Background in optimization, simulation, or physics-informed ML.
- Experience applying ML in engineering-heavy domains (civil, HVAC, mechanical, energy systems).
- Track record of mentoring or technically leading ML initiatives.
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.
Senior Machine Learning Engineer in London employer: AECOM
Contact Detail:
AECOM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with AECOM employees on LinkedIn. Building relationships can open doors that applications alone can't.
✨Tip Number 2
Prepare for those interviews! Research AECOM's projects and values, and think about how your skills can contribute to their mission. Practice common interview questions and be ready to showcase your ML expertise.
✨Tip Number 3
Show off your portfolio! If you've got past projects or contributions to open-source, make sure to highlight them. Real-world examples of your work can set you apart from the crowd.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the AECOM team. Don’t miss out!
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for AI and engineering shine through. We want to see how your bold ideas can contribute to our mission of delivering a better world!
Tailor Your Experience: Make sure to highlight your relevant experience in developing and deploying ML models. We’re looking for specific examples that demonstrate your expertise and how it aligns with the role.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your skills and experiences are easy to understand.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for this exciting opportunity.
How to prepare for a job interview at AECOM
✨Know Your ML Models Inside Out
Make sure you can discuss your experience with developing and deploying machine learning models in production. Be ready to explain the intricacies of your model design, optimisation techniques, and how you've tackled real-world performance trade-offs.
✨Showcase Your Problem-Solving Skills
Prepare to tackle complex, ambiguous problems during the interview. Think about how you would approach these challenges and be ready to share examples from your past work where you successfully translated vague issues into scalable ML solutions.
✨Communicate Clearly and Confidently
Practice explaining complex modelling decisions in simple terms. You’ll need to communicate effectively with diverse stakeholders, so being able to break down technical jargon will show that you can bridge the gap between technical and non-technical team members.
✨Collaborate and Connect
Highlight your experience working with cross-functional teams, especially with product managers and engineers. Discuss how you’ve embedded AI capabilities into platforms and how collaboration has led to successful project outcomes.