Anson McCade
Machine Learning Engineer
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
About the Company
I’m currently working on an exciting opportunity for a Machine Learning Engineer to join a rapidly growing AI organisation working on some genuinely high-impact projects across National Security, Government and cutting-edge technology.
About the Role
This is a great opportunity for someone who enjoys taking ML out of the lab and into production, working across software engineering, machine learning and cloud infrastructure.
Responsibilities
- Building and deploying production-grade ML software, tools and infrastructure
- Developing scalable and reusable ML solutions
- Working closely with engineers, data scientists and clients
- Contributing to technical architecture and solution design
- Helping define best practices for deploying ML at scale
- Advising clients and translating complex ML concepts into practical solutions
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.
Qualifications
- Strong Python and software engineering experience
- Experience operationalising ML models using Scikit-learn, TensorFlow or PyTorch
- Strong understanding of the machine learning lifecycle
- Experience with AWS, Azure or GCP
- Hands-on experience with Docker and Kubernetes
- Solid understanding of ML fundamentals, probability and statistics
- Strong communication skills and the ability to work with both technical and non-technical stakeholders
Required Skills
Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Strong Python and software engineering experience
- Experience operationalising ML models using Scikit-learn, TensorFlow or PyTorch
- Strong understanding of the machine learning lifecycle
- Experience with AWS, Azure or GCP
- Hands-on experience with Docker and Kubernetes
- Solid understanding of ML fundamentals, probability and statistics
- Strong communication skills and the ability to work with both technical and non-technical stakeholders
Preferred Skills
- Experience with AWS, Azure or GCP
- Hands-on experience with Docker and Kubernetes
Note: Due to the nature of the work, candidates may need to be eligible for UK Developed Vetting (DV).
“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