Xcede
Senior Machine Learning Engineer
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Machine Learning Engineer
In the office ~x2/3 days a week in London
About the Company
We’re working with a specialist AI consultancy that delivers tailored machine learning systems for organisations operating in high-complexity domains. Their clients span industries such as finance, defence, legal services, government, and energy. The core focus is on building safe, production-ready AI that performs in demanding real-world settings.
This is a fast-paced and technically rigorous environment, ideal for someone who enjoys solving practical challenges, contributing to engineering excellence, and building reliable infrastructure around machine learning systems.
What You’ll Be Doing
- Design, build, and maintain machine learning pipelines that are robust, scalable, and suitable for production environments
- Develop internal tooling and infrastructure to support model deployment, monitoring, and retraining workflows
- Contribute across the AI delivery lifecycle, including system architecture, integration planning, and performance tuning
- Work closely with clients and cross-functional teams to ensure technical solutions meet real-world constraints and expectations
- Help define engineering standards, mentor more junior developers, and support internal capability building
- Collaborate on improving internal processes and best practices for MLOps and AI platform delivery
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What They’re Looking For
- Strong programming skills in Python with experience building backend systems
- Background in developing infrastructure to support machine learning projects
- Practical experience deploying models using frameworks such as PyTorch, TensorFlow, or scikit-learn
- Familiarity with tools like Docker and Kubernetes for containerised deployments
- Experience working with cloud platforms such as AWS, Azure, or GCP, including an understanding of cost, scaling, and security trade-offs
- Good understanding of machine learning fundamentals, including evaluation metrics and modelling best practices
- Clear communication skills and the ability to collaborate effectively with both technical and non-technical teams
- Bonus: experience in fast-moving or delivery-focused environments where pragmatism and flexibility are key
Get help with your application
Your very own career expert that helps elevate your application to the next level.
If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location