Staff Machine Learning Engineer

Staff Machine Learning Engineer

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Own the decisioning system for real-time transaction scoring and fraud prevention.
  • Company: Join MoonPay, a leading crypto company with a high-performance culture.
  • Benefits: Competitive salary, equity options, flexible time off, and wellness perks.
  • Other info: Dynamic hybrid work environment with excellent growth opportunities.
  • Why this job: Make a real impact in the fast-paced world of crypto and AI.
  • Qualifications: Experience in real-time serving and systems thinking is essential.

The predicted salary is between 63000 - 77000 £ per year.

About MoonPay

MoonPay 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 meet 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 Moonpay.

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 budget.
  • Design 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 reversible.
  • Own 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 mechanisms.
  • Systems 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 behaviour 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 MoonPay
  • Pay-for-performance equity bonus: those who drive outsized outcomes receive outsized rewards
  • Moonshot award: we honour 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 remotely 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

Staff Machine Learning Engineer employer: Jackalope Digital LLC

MoonPay is an exceptional employer that champions innovation and accountability, offering a dynamic work culture where employees are empowered to tackle challenging problems and make a real impact. With a competitive salary package, equity opportunities, and a strong focus on employee growth through structured development programs, MoonPay fosters an environment that values both personal and professional advancement. Located in London, the hybrid working model allows for flexibility while enjoying comprehensive benefits like enhanced parental leave, wellness memberships, and a supportive community of builders dedicated to shaping the future of value movement.

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Contact Details:

Jackalope Digital LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Machine Learning Engineer

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Jackalope Digital LLC or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Jackalope Digital LLC.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Jackalope Digital LLC.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Jackalope Digital LLC that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Staff Machine Learning Engineer

Real-time Serving
High-Availability Services
Systems Thinking
Engineering Craft
Feature and Data Pipelines
Ambiguity Management
Decision Explainability

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Jackalope Digital LLC.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Jackalope Digital LLC and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Jackalope Digital LLC

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Jackalope Digital LLC uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.