Senior Machine Learning Engineer SurePay
Location: Hybrid from Utrecht FinTech SaaS Fraud & AML Discovery Team 1 Day/Week in Office
Build fast. Train smart. Stop fraud before it happens.
At SurePay, we’ve made a name for ourselves protecting payments. We’re the team behind IBAN-Name Check, used in over 10 billion transactions across Europe. Now, we’re building something new. A fraud and anti-money laundering (AML) product suite that stops threats before they happen.
We’re looking for a Senior Machine Learning Engineer to join our Discovery team. Someone who’s been in the trenches, built real systems, and knows what it takes to bring machine learning to production securely, scalably, and with purpose. We need someone that combines hands-on experience deploying ML solutions to production with enough technical seniority to lead a new data department and help us to shape our product vision
The opportunity
This isn’t a research lab or a tuning task. This is product-led ML. You’ll work with real transaction data (anonymized for data processing), partner with engineers and data scientists, and help us uncover signals, validate assumptions, and design the core ML systems that power fraud detection at scale.
We’re dealing with:
Real-time signals
Messy, high-volume financial data
High-stakes decisions
Model explainability and ethical AI
And we need someone who can build confidently in that space.
What you’ll do
Design and build end-to-end ML systems from data ingestion to model deployment
Prototype models that test fraud and AML hypotheses using real data
Train, evaluate, and optimise models using frameworks like PyTorch, TensorFlow, Scikit-learn, and Spark
Work closely with data scientists and product managers to ensure models solve the right problems
Implement automation, CI/CD pipelines, and MLOps practices for repeatable ML delivery
Collaborate on infrastructure and data storage architecture (we’re AWS-native and IaC by default)
Focus on model explainability, fairness, and responsible AI
Your role will be pivotal to create SurePay's ML foundations and mentor others as the team scales
What we’re looking for
You’ve done this before and not just once. You’ve shipped machine learning systems into production, handled messy data, iterated quickly, and made smart trade-offs between theory and practice. You work well in fast-moving, high-trust teams and care about building things that work and last.
Must-haves
8+ years of professional experience in Machine Learning or Data Science roles with a strong engineering focus
Deep knowledge of ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, Spark)
Demonstrated experience designing and deploying ML pipelines in production environments
Solid understanding of cloud platforms (AWS preferred), infrastructure as code, and containerised deployment
Familiarity with CI/CD practices for ML, MLOps tools, and model lifecycle management
Strong instincts for model performance, explainability, and ethical design
Excellent communication and collaboration skills. You’ll work across product, data, and engineering
Bonus points
Experience working in fraud prevention, financial crime, AML, or high-noise domains
Familiarity with platforms like NICE Actimize, RiskShield, Pega, or FCRM
Knowledge about LLMs and how to deploy them to production
Backend engineering, data infra, or architectural experience
What you’ll get
8% holiday allowance + 8% personal benefits budget (can be added to salary, training, or more time off)
25 holidays + flexible working hours + hybrid setup
MacBook Pro, iPhone, and any extra tools you need
NS Business Card & travel cost coverage
Learning budget, pension plan, and strong development culture
A flat, friendly, high-trust culture where you’re given ownership, autonomy, and support
Why now?
This isn’t just another ML role. This is a chance to shape an entire product, building machine-learning systems to protect society by detecting financial crime in real time, enabling a safer and more trusted financial ecosystem. You’ll be here from the start. Helping us design the foundation and scale it up with care.
Apply now or reach out to chat, we’d love to hear from you.
About SurePay
Founded in 2016
130 employees
30 nationalities
Flat organisation and no hierarchy
SurePay makes payments easier, more personal and even more secure. We are a fast-growing FinTech SaaS company and have secured our Series A funding in September 2021. SurePay stems from an innovation program of Rabobank, started in July 2016 and has been an independent BV since the beginning of 2020. SurePay is backed by two leading investors: Rabo Investments and Carlyle Europe Technology Partners. Both are highly experienced in scaling international B2B SaaS and FinTech companies. Their support reinforces SurePay’s mission to prevent payment fraud globally and accelerate our international growth.
SurePay's core values are; We Care, Build Together, Think Forward and Be Responsible. These core values are the driver's of our culture and can be seen as guidelines on our beliefs and behaviour. It defines what we find important as a company and the way we work together everyday.
We Care: We are a supportive employer and understand that health, family and safety is what really matters. We care about our employees, customers, partners and end-users. Therefore we value creating a safe workspace where everybody can be their authentic self and where we, together, work on the same mission to provide safer payments.
Build Together: We believe in teamwork and strive towards the best results together with employees and customers. Our diversity, both personal and professional, is one of our key strengths.
Think Forward: We are frontrunners and are on top of our game. Our customers can rely on innovative solutions to service their current and future needs. With a problem solving mindset, we anticipate challenges and adapt to a fast changing environment.
Be Responsible: We all contribute to reaching our mission of reducing fraud and misdirected payments, leading to a positive impact on society. We take responsibility, show ownership and make honest decisions.
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