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aimlroles

Senior MLOps Engineer (Parental cover, 16 months)

LEGO lego.com Open · verified Nov 1, 2026
London Full-time Senior ML Platform & Ops

At a glance

Senior ML Platform & Ops role at LEGO. London · full-time · no salary stated · we estimate £96,000–£155,000.

Estimated pay

LEGO has not published a salary for this role. The figure below is our estimate, not theirs.

£96,000 – £155,000
What the middle half of senior ML platform & ops roles in London paid, among postings that did state a salary.
Worked out from 5 postings that stated pay, median £96,000. Last updated Oct 27, 2026.
RoleML Platform & Ops
SenioritySenior
LocationLondon
EmploymentFull-time
PostedOct 15, 2026 · 2w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Put customer-focused machine learning models into production, then keep their deployment and monitoring dependable
  • Improve the operating framework for live models and address reliability concerns, dependencies and operational risks
  • Coordinate data scientists, data engineers and software engineers as they turn models into production solutions
  • Explain deployment choices, system dependencies and live-production risks to technical and non-technical partners
  • Create repeatable processes for model upkeep, monitoring and responding to operational incidents

What you bring

  • You have deployed and monitored machine learning models in live production settings
  • You have strengthened MLOps practices while managing reliability and operational risks
  • You have worked across data science, data engineering and software engineering to launch production ML solutions
  • You can explain deployment decisions, dependencies and production risks to both technical and non-technical audiences

Who this fits

This senior role suits an engineer with practical experience supporting machine learning models through their production lifecycle. It is a sixteen-month parental-cover position based in London, with an office-based workplace and the option to work from home up to two days per week.

From the employer

Job Description


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.


Insurances – All colleagues are covered by our life and disability insurance which provides protection and peace of mind.


Wellbeing - We want our people to feel well and thrive. We offer resources and benefits to nurture physical and mental wellbeing along with opportunities to build community and inspire creativity.


Colleague Discount – We know you'll love to build, so from day 1 you will qualify for our generous colleague discount.


Bonus - We do our best work to succeed together. When goals are reached and if eligible, you'll be rewarded through our bonus scheme.


Your workplace: Your workplace will be the office, store or factory specified in this advert.


Hybrid Working: Our hybrid work model, Best of Both offers you the option of flexibility to work from home up to two days per week. Your People Leader will discuss the principles of the model, including how this option applies to your role and team.

Learn more about our benefits, culture and workplace experience here


Children are our role models. Their curiosity, creativity and imagination inspire everything we do. We strive to create a diverse, dynamic and inclusive culture of play at the LEGO Group, where everyone feels safe, valued and they belong.


The LEGO Group is highly committed to equal employment opportunity and equal pay and seeks to encourage applicants from all backgrounds (eg. sex, gender identity or expression, race/ethnicity, national origin, sexual orientation, disability, age and religion) to apply for roles in our team.


The LEGO Group is fully committed to Children’s Rights and Child Wellbeing across the globe. Candidates offered positions with high engagement with children are required to take part in Child Safeguarding Background Screening, as a condition of the offer.


Thank you for sharing our global commitment to Children’s Rights.


Just imagine building your dream career.

Then make it real.

Join the LEGO® team today.


Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

ML Platform & Ops

Find me work

By the team behind aimlroles.

Find me work
Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind aimlroles.