Staff Machine Learning Engineer
London · London, United Kingdom
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Tech › Data › Data Science — team source
Department: Tech › Data › Data Science
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Do you now, or will you in the future require visa sponsorship to be legally employed in the UK? We can usually offer visa sponsorship, but it's helpful to know now so we can plan accordingly.
From the employer’s application form
What you’ll work on
Full postingBuild ranking and personalisation systems that reach the right users in real time
Design reward and payout infrastructure balancing user motivation, cost and business value
Model user behaviour with time-series and sequence systems
Measure impact with A/B testing, causal inference and uplift modelling
Run ML pipelines, training, serving and monitoring
From the employer’s posting
Ranking and personalisation systems that reach the right users in real time
Reward and payout infrastructure balancing user motivation, cost, and business value
Behavioural prediction through time-series and sequence systems
Measurement and validation using A/B testing, causal inference, uplift modelling
ML infrastructure: pipelines, training loops, serving, monitoring
What you’ll bring
All qualificationsCore experience
- Shipped production ML systems end to end, from data pipeline to live serving
- Causal inference skills: propensity scoring, uplift modelling, contextual bandits
- Experience building systems for high-volume behavioural data and real-time inference
- Cross-functional work with engineering, product and data science teams
Qualification wording
Shipped production systems end to end, from formulation through impact measurement
Causal thinking: propensity scoring, instrumental variables, contextual bandits, uplift modelling
Scale experience: built systems handling high-volume behavioural datasets and real-time inference
Cross-functional: collaborate across engineering, product, and data science teams on measurement and infrastructure
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 9, 2026 · 20 days ago
- Recorded sightings
- 24
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Oct 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
This isn’t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We’re aiming to become Germany’s second bootstrapped unicorn. Almedia is already Europe’s #3 fastest-growing company in 2025 (FT1000).
We are building the future of marketing by rewarding our community of over 95 million users for engaging with our advertisers’ products. We are offering a new way to acquire users for the biggest companies in the world.
Staff Machine Learning Engineer
London, King's Cross
Top-of-market compensation
The Role
You'll take ownership of designing, building, and shipping production-grade systems that power ranking, personalisation, and reward structures in real time. You work hands-on with a small, high-ownership team. You have real influence over how we build our infrastructure as we grow it together.
You spot leverage points others miss: systems that shift behaviour, ranking that balances user value and business sustainability, measurement frameworks that prove what actually works. You own these end to end.
What You'll Own
Ranking and personalisation systems that reach the right users in real time
Reward and payout infrastructure balancing user motivation, cost, and business value
Behavioural prediction through time-series and sequence systems
Measurement and validation using A/B testing, causal inference, uplift modelling
ML infrastructure: pipelines, training loops, serving, monitoring
Technical leadership and mentorship on shipping discipline and impact
What We're Looking For
Shipped production systems end to end, from formulation through impact measurement
Full-stack capability: data pipeline to live serving to monitoring and decay
Causal thinking: propensity scoring, instrumental variables, contextual bandits, uplift modelling
Scale experience: built systems handling high-volume behavioural datasets and real-time inference
Published work or equivalent research discipline
Builder's mindset: energised by shipping. Zero-to-one experience valued
Cross-functional: collaborate across engineering, product, and data science teams on measurement and infrastructure
Why This Matters
Real behavioural sequences. Billions of user decisions across multiple games. Your systems handle cold start, sparse reward, imbalanced value distributions. Both measurement rigour and systems thinking matter here.
Why Almedia
Profitable from launch. Higher revenue per employee than Big Tech.
Small team by design. Every hire raises the bar.
Top-of-market compensation including substantial equity.
Real behavioural data at scale. Billions of user interactions, millions of daily active users.
We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.
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London, United Kingdom
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