Cognify Search
MLOps Engineer

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MLOps Engineer
Salary: Up to £65k + bonus
Location: London (1x per week)
I'm currently partnering with one of the UK's leading consumer technology businesses as they continue to invest heavily in their Data & AI capabilities.
They're looking for an MLOps Engineer to help build and scale the infrastructure that enables machine learning across the organisation. Working alongside Data Scientists, Data Engineers, and Software Engineers, you'll play a key role in taking ML models from experimentation through to reliable, production-ready deployment.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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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.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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.
This is an opportunity to join a highly collaborative engineering environment where you'll influence the future of the ML platform while working with modern cloud technologies and best engineering practices.
What you'll be doing
- Building and scaling cloud-native infrastructure for machine learning
- Designing CI/CD pipelines to automate model deployment
- Developing tooling that enables Data Scientists to deploy models efficiently
- Improving model monitoring, performance, and reliability in production
- Building infrastructure using Infrastructure as Code
- Collaborating across Engineering and Data teams to improve the end-to-end ML lifecycle
- Helping shape the future direction of the company's MLOps capability


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Tech Stack
- Python
- AWS (SageMaker, ECS, Lambda, S3, Glue)
- Terraform
- FastAPI
- Snowflake
- SQL
- GitHub Workflows
- Grafana
- Metaplane
📩 Feel free to message me directly for a confidential conversation: daniel@cognifysearch.com
“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
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