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- Tasks: Lead the design of advanced AI/ML models that make a real impact.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Enjoy comprehensive health benefits, flexible work options, and paid time off.
- Other info: Dynamic team environment with opportunities for mentorship and career growth.
- Why this job: Shape the future of engineering with cutting-edge machine learning solutions.
- Qualifications: Master's or PhD in relevant fields and proven ML model experience required.
The predicted salary is between 60000 - 80000 ÂŁ per year.
Job Responsibilities
- 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.
Interview Process
- Take‑home challenge: a hands‑on task to assess problem‑solving and technical skills.
- Combined technical and cultural interview (in‑person).
- Whiteboard interview: 1‑hour with two engineers to discuss your solution to the take‑home challenge.
- Culture fit: 30‑minute meeting with our leadership team.
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, optimisation, and evaluation beyond standard off‑the‑shelf approaches.
- Strong intuition for model failure modes, generalisation, 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 optimisation, 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.
Benefits
- Medical, dental, vision, life, AD&D, and disability benefits.
- Paid time off, leaves of absence, and voluntary benefits.
- Flexible work options, well‑being resources, and an employee assistance programme.
- Retirement savings plan and employee stock purchase plan.
Senior Machine Learning Engineer employer: AECOM
Contact Detail:
AECOM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Get ready for that take-home challenge! Make sure you understand the problem and break it down into manageable parts. Show off your skills in Python and ML frameworks like PyTorch or TensorFlow, and don’t forget to document your thought process.
✨Tip Number 2
During the combined technical and cultural interview, be yourself! We want to see how you think and communicate. Prepare to explain your modelling decisions clearly, as this will show your ability to collaborate with product managers and engineers.
✨Tip Number 3
For the whiteboard interview, practice explaining your solutions out loud. It’s not just about getting the right answer; it’s about how you approach problems and articulate your thought process. This is your chance to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and engaged in the process.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with ML models, Python, and any relevant projects that showcase your skills in engineering domains.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of your past work, especially those that demonstrate your ability to tackle complex problems and deliver high-impact ML solutions.
Showcase Your Technical Skills: In your application, don't shy away from showcasing your technical prowess. Mention the ML frameworks you’ve worked with, and any unique approaches you've taken in model design and optimisation that set you apart from the crowd.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. This way, we can easily track your application and ensure it gets the attention it deserves!
How to prepare for a job interview at AECOM
✨Master the Take-Home Challenge
Before your interview, make sure to thoroughly understand the take-home challenge. Break down the problem, outline your approach, and document your thought process. This will not only help you solve the task effectively but also prepare you for discussing your solution during the whiteboard interview.
✨Showcase Your Technical Skills
During the technical interview, be ready to dive deep into your experience with Python and ML frameworks like PyTorch or TensorFlow. Prepare examples of past projects where you developed and deployed ML models, focusing on the challenges you faced and how you overcame them.
✨Communicate Clearly and Confidently
As a Senior Machine Learning Engineer, you'll need to explain complex concepts to various stakeholders. Practice articulating your modelling decisions and trade-offs in simple terms. This will demonstrate your ability to communicate effectively and ensure everyone is on the same page.
✨Emphasise Collaboration and Culture Fit
In the culture fit interview, highlight your experience working with cross-functional teams, including product managers and engineers. Share examples of how you've collaborated to embed AI capabilities into products, showcasing your teamwork skills and alignment with the company's values.