Staff Machine Learning Engineer

United States Digital Space LLC; Greater London; On-site; GBP 140,000 - 170,000; Full time

Benefits offered by this job

Competitive salary

Equity package

Pension

Remote or Hybrid work

Annual training budget

Private healthcare

Wellness benefits

Lunch credits

Job summary

United States Digital Space LLC in London is seeking a Staff Machine Learning Engineer to own the real-time decisioning platform for fraud detection. You'll build and maintain end-to-end ML lifecycle, from data pipelines to in-flight scoring, with a focus on low latency and reliability.

Join a high-velocity team that values ownership, rigorous reviews, and fast impact. Hybrid work (office 1–2 days per week) and access to cutting-edge AI tools await.

Qualifications

• Real-time serving with high-availability requirements on critical paths.
• Systems thinking: holistic architecture, failure points, graceful degradation.
• Engineering craft: well-typed, tested code that handles out-of-order events.
• End-to-end ownership of feature/data pipelines and metrics reconciliation.
• Ability to turn ambiguous problems into shipped, impactful work.

Responsibilities

• Own the in-flight transaction scoring services and latency budgets.
• Develop feature infrastructure across batch, near-real-time, and in-request paths.
• Maintain training-serving alignment and monitor production model behavior.
• Mature replay, shadow, and staged-rollout tooling for safe updates.

Skills

Real-time serving

High-availability services

Latency budget design

Systems thinking

Engineering craft

End-to-end pipelines

Ambiguity and influence

Tools

GCP

BigQuery

Bigtable

Memorystore

Vertex AI

Kubernetes

Job description

About the companythe company is for builders with something to prove.

This isn't a "work on cool crypto stuff" company. It's a high-standards, high-velocity, high-accountability company building the operating system for value movement. If the internet moves information, we move value: crypto, stablecoins, tokenized assets, and whatever comes next. Four offerings make that real: fund, tokenize, trade, and spend. 30M+ customers and 500+ ecosystem partners run on us. Licensed in the U.S. Regulated across the UK, EU, Canada, and Australia.

AI is the default operating mode here. It's woven into every role, and we expect you to use it daily. It handles the manual work so you can deliver on what actually matters.

You'll thrive here if outcomes excite you more than process, if impact motivates you more than titles, and if you want hard problems, real ownership, and teammates who love winning, building, and doing it together.

The bar is high. The pace is real. We're building for what's next, for humans and agents.

Recent recognition:Forbes' America's Best Startup Employers 2026 . 2nd in Crypto Services on Fortune's inaugural Crypto 100,The Sunday Times Best Places to Work two years running.

Research has shown that women are less likely than men to apply for this role if they do not have experience in 100% of these areas. Please know that this list is indicative, and that we would still love to hear from you even if you feel that you are only a 75% match. Skills can be learned, diversity cannot.

Locations Supported

London, UK

Relocation available: No

Work pattern: Hybrid: our teams meets in the office ~1-2 days a week

About the Opportunity

Every transaction we process requires a real-time decision. Declining a legitimate transaction leaves a customer stuck at the point of purchase, while approving a fraudulent one carries a direct cost.

This role owns the decisioning system and underlying platform. From the serving path and feature infrastructure to the underlying models and the machinery required to make safe, live updates. You will continuously improve the platform and our day to day workflows, rather than treating these as secondary projects.

As a Staff Machine Learning Engineer, you will hold a hands-on technical position. You will be part of a team that builds, ships, and maintains the entire machine learning lifecycle.

Our main focus is fraud detection and prevention, an adversarial domain where opponents constantly adapt and feedback arrives in the form of financial impact. Alongside, this we build broader capabilities to enable machine learning across the company.

Lead through ambiguity

Turn vague problems into well-defined solutions and bring people with you.Set the technical bar through rigorous reviews, clear standards, and lasting engineering habits.

Build and scale the platform

Develop feature infrastructure across batch, near-real-time, and in-request paths, managing specific freshness budgets for each.Maintain alignment between training and serving to ensure models behave in production exactly as they did offline.Integrate feedback loops to capture every decision and its outcome, including blocked transactions where results are counterfactual.Scale the platform as volume and model complexity grow, ensuring operational load remains manageable.

Decide in real time

Own the services that score transactions in-flight, inside a hard latency budgetDesign the degraded paths: what we answer when the model can't, and who agreed that policy

Ship safely, continuously

Mature the replay, shadow and staged-rollout tooling until changing a live model is routine and reversibleOwn models across their lifecycle, from training through to retirement, and catch decay long before losses confirm it

About You

Must-have experience and skills

Real-time serving. You have built and operated high-availability services that execute within strict latency budgets on critical paths, and you’ve designed robust fallback mechanismsSystems thinking. You view the architecture holistically: identifying failure points, managing graceful degradation, and ensuring the system remains responsive even when dependencies fail. You build the feedback loops that allow a system to learn from its own decisions.Engineering craft. You write code other people are happy to inherit — tested, typed, and correct when events arrive twice, late, or out of order. Adding the next feature to something you built is fast and painless.Pipelines in production. You have owned feature or data pipelines end-to-end, including troubleshooting cases where offline and production metrics diverged and resolving the underlying discrepancies.Ambiguity and influence. You've taken a problem nobody had scoped and turned it into work that shipped, and raised the level of the engineers around you while doing it.

Nice-to-have experience

Decision explainability. You've built systems where the reason for a decision mattered as much as the decision: audit trails, per-layer attribution, llm-driven analyses, or defending a model's behaviour to a non-technical audience.Anomaly detection. You have developed systems to detect novel attack patterns and emerging abuse without existing labels, identifying suspicious behavior relative to historical baselines.Familiarity with our stack: GCP, BigQuery, Bigtable, Memorystore, Vertex AI, Kubernetes.

Benefits & Perks

• Competitive salary package
• Equity package: financial freedom starts with our employees, so all employees have ownership at the company
• Pay-for-performance equity bonus: those who drive outsized outcomes receive outsized rewards
• Moonshot award: we honor exceptional impact. 10 employees twice a year, each earning a $250,000 equity grant
• Pension: employer contributions from day one
• Employee referral program: refer great people, earn 10K in USDC
• Flexible Time Off: choose when to work and when to switch off
• Birthday leave: take the day off to celebrate you
• Enhanced parental leave: more time with family, no second thought
• Hybrid working schedule: work fully remote or from your nearest Moonbase
• Commuter benefits: public transport to and from the office
• Private healthcare benefits: to protect you and your loved ones
• Wellhub wellness membership: access to gyms, studios, classes, and wellness apps in one membership
• Unlimited enterprise access to the latest AI tools: Claude, ChatGPT, Gemini and whatever's next
• Lunch credit: meals covered on the days you're in the office
• Home office setup allowance: build the home office of your dreams
• Remote working allowance: those working fully remotely get a little extra for utilities
• Monthly product budget and zero-fee crypto transactions
• $1,000 Annual training budget: we support your learning journey
• High Potential Program: structured development, mentorship and stretch opportunities
• Regular remote company offsites: high-impact in-person sessions and hackathons
• (Ireland) Cycle to Work scheme: tax-efficient bike, gear, and safety kit
• (UK) EV Salary Sacrifice: lease an electric vehicle through pre-tax salary