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Staff Machine Learning Engineer

London · London, United Kingdom

Pay
Pay not listed
Work setting
On-site — work setting source
Location type: On-site
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Employment
Full-time — employment source
Employment type: Full-time
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Team
Tech › Data › Data Science — team source
Department: Tech › Data › Data Science
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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.
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What you’ll work on

Full posting
  • Build 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 qualifications

Core 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

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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

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Job description

View original posting ↗

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.

Source details

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Location & working pattern

London, United Kingdom

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