Senior MLOps Engineer; Parental cover

Position: Senior MLOps Engineer (Parental cover, 16 months)
Location: Greater London

## Senior MLOps Engineer (Parental cover, 16 months)
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London:
Full time:
Posted Today:

** Job Description**#LI-KO1  Just imagine turning millions of customer interactions into production-ready machine learning models that deliver more relevant, personalised experiences. Then make it real.  
** About the role
** As our Senior MLOps Engineer, you’ll bring machine learning models out of the workshop and into dependable production environments during this 16-month parental cover. You’ll make deployment and monitoring smoother, strengthen our machine learning operations framework and help manage risks across live systems. Along the way, you’ll connect data science, data engineering and software engineering, turning customer models into reliable solutions that can grow without losing their balance.

** Required Qualifications**
* ** Deployed
* * and monitored machine learning models in production environments.
* ** Improved
* * machine learning operations frameworks while managing reliability and operational risks in live systems.
* ** Partnered
* * with data scientists, data engineers and software engineers to deploy production machine learning solutions.
* ** Explained
* * machine learning deployment decisions, dependencies and production risks to technical and non-technical partners.  
** Preferred Qualifications**
* ** Operationalised
* * customer models through a Customer Data Platform.
* ** Developed
* * machine learning models using large-scale customer, behavioural, customer relationship management or marketing data.
* ** Built
* * or productionised machine learning models for marketing targeting and personalised experiences.
* ** Documented
* * model deployment, monitoring and incident-handling processes for engineering and product teams.  
** What you’ll build
*** Production workflows that make model deployment and monitoring reliable and repeatable.
* Stronger operational practices that keep live systems healthy and maintainable.
* Clear processes for handling model dependencies, production risks and operational incidents.
* Practical connections between customer models, behavioural data and marketing technology.
* Shared ways of working across data science, data engineering and software engineering.

If you’ve moved machine learning models into production and cared for them throughout their lifecycle, you’ll feel at home here. What matters most is practical engineering experience, thoughtful technical communication and a keen eye for keeping production systems steady.  
** Life on the team
** You’ll work alongside colleagues across data science, data engineering, software engineering, product and marketing technology. Everyone shares responsibility for how models behave once they’re live. Curiosity is welcome, reliability matters and complex challenges are easier when people build the answer together. You’ll add your technical perspective while helping different audiences see how the pieces connect.  
** What success looks like
** You’ll establish dependable approaches to deploying, monitoring and maintaining customer-focused machine learning models. You’ll strengthen our operational framework, spot dependencies earlier and reduce risks across live environments. By bringing teams and technologies together, you’ll leave behind solutions that are easier to understand, support and improve.  Applications are reviewed on an ongoing basis. However, please note we do amend or withdraw our jobs and reserve the right to do so at any time, including prior to any advertised closing date.

So, if you're interested in this role we encourage you to apply as soon as possible.
** What’s in it for you?
** Here is what you can expect:  
** Family Care Leave** - We offer enhanced paid leave options for those important times.  
**…