Staff Machine Learning Engineer

Almedia

London, United Kingdom

On-site

Who this role is best for

Strong fit for candidates with hands-on ML infrastructure experience who can balance user behavior and business metrics, and who thrive in a small, high-impact team environment in London.

Best fit for

Candidates with end-to-end system ownership experience and a background in causal inference and real-time data processing
— “Shipped production systems end to end, from formulation through impact measurement”
Individuals who have built scalable ML systems and understand the challenges of sparse reward and cold start scenarios
— “Your systems handle cold start, sparse reward, imbalanced value distributions”
Candidates who have experience in technical leadership and mentoring within a small, high-ownership team setup
— “Technical leadership and mentorship on shipping discipline and impact”

Things to consider

This role requires a high level of cross-functional collaboration across engineering, product, and data science teams
— “Collaborate across engineering, product, and data science teams on measurement and infrastructure”
The role may demand significant on-site presence in London, given the location and team structure
— “London, King's Cross”

How to stand out

Emphasize experience in building real-time inference systems and handling high-volume behavioral datasets
— “Scale experience: built systems handling high-volume behavioural datasets and real-time inference”
Demonstrate your ability to apply causal inference techniques, such as uplift modeling and instrumental variables
— “Causal thinking: propensity scoring, instrumental variables, contextual bandits, uplift modelling”
Showcase your involvement in measurement frameworks and A/B testing to align with the role's focus on validation
— “Measurement and validation using A/B testing, causal inference, uplift modelling”
Demonstrate your capability in full-stack ML infrastructure, from pipelines to monitoring and decay
— “Full-stack capability: data pipeline to live serving to monitoring and decay”

Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design and build production-grade systems
ship systems end to end
measure impact
build ML infrastructure
mentor team members

Typical background

machine learning engineerdata scientistsoftware engineer

Skills & requirements

Required

Machine LearningRanking SystemsPersonalizationReward StructuresReal-time SystemsBehavioral PredictionTime-seriesSequence SystemsMeasurement FrameworksA/B TestingCausal InferenceUplift ModelingML InfrastructurePipelinesTraining LoopsServingMonitoringTechnical LeadershipMentorship

Preferred

Full-stack CapabilityCausal ThinkingScale ExperiencePublished WorkZero-to-one ExperienceCross-functional Collaboration

Stack & domain

Machine LearningRankingPersonalisationReward StructuresReal-time SystemsFull-stack CapabilityData PipelineLive ServingMonitoringDecayCausal ThinkingPropensity ScoringInstrumental VariablesContextual BanditsUplift ModellingML InfrastructurePipelinesTraining LoopsServingTechnical LeadershipMentorshipShipping DisciplineImpactTake OwnershipDesignBuildShipMeasureValidatePredictMonitorMarketingData Science

About the role

Original posting from Almedia via Ashby

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: Almedia careers (Ashby)