Harnham
MLOps Engineer

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Senior MLOps Engineer
London (Hybrid) | £75,000 to £85,000 + Bonus + Benefits
Are you a hands-on MLOps Engineer who enjoys building scalable platforms rather than simply maintaining them? This is a chance to take ownership of the infrastructure behind a growing AI and machine learning environment, helping shape the future of production ML systems while working closely with data scientists and machine learning engineers.
The Company
They are a specialist AI and data consultancy that develops machine learning, predictive analytics and NLP solutions for a diverse client base. As their platform and client demand continue to grow, they are investing heavily in the infrastructure, tooling and processes that support production AI services. You'll join a collaborative technical team where you'll have genuine influence over architectural decisions and platform direction.
The Role
You will play a key role in building and scaling the infrastructure that underpins production AI and machine learning solutions.
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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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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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.
Responsibilities Include:
- Developing and maintaining scalable MLOps infrastructure
- Owning orchestration platforms such as Dagster, Airflow or Prefect
- Working directly with Python applications and services
- Managing Kubernetes-based production environments
- Improving monitoring, observability and platform reliability
- Implementing infrastructure as code using Terraform or Bicep
- Enhancing CI/CD processes and deployment automation
- Partnering with data scientists and ML engineers to support production workloads
Your Skills & Experience
- Strong commercial experience working in MLOps environments
- Excellent Python software engineering skills
- Hands-on experience with Dagster, Airflow, Prefect or similar orchestration tools
- Proven Kubernetes experience in production
- Experience with monitoring, observability and deployment tooling
- Infrastructure as code expertise, ideally Terraform or Bicep
- Understanding of production machine learning, predictive analytics or NLP systems


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Desirable Experience:
- Azure cloud technologies
- LLM infrastructure
- Vector databases
- GPU compute environments
What They Offer
- £75,000 to £85,000 salary
- Up to 10% bonus
- Hybrid working with 1 to 2 days per week in the London office
- Private healthcare and additional benefits
- Six-monthly reviews and progression opportunities
- High levels of ownership and technical autonomy
- The opportunity to help build the next generation of AI infrastructure
How to Apply
If you're looking for a Senior MLOps Engineer opportunity where you can combine Python, Kubernetes and ML platform expertise to make a tangible impact, apply today to find out more.
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