Staff Machine Learning Engineer - Munich

PPRO; München; Hybrid; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid working

€1,000 learning budget

Insurance - various insurances

Enhanced family leave

Gym membership subsidy

Mental health platform

Job summary

PPRO is seeking a Staff Machine Learning Engineer to shape ML strategy and scale across the payments platform. You will lead architectural decisions, build scalable ML infra, and partner with product, data, and platform teams to deploy production-grade ML solutions.

You will mentor senior engineers, drive ML governance, and design experimentation strategies that improve authorization, routing and retry logic across our payments stack.

Qualifications

• Demonstrated experience designing and shipping ML systems that serve multiple products or teams.
• Proven ability to drive technical decisions across teams without direct authority.
• Expert-level command of classical ML and practical evaluation frameworks.

Responsibilities

• Define ML technical strategy and multi-quarter roadmap for ML-driven optimization.
• Architect and lead shared ML infrastructure and model serving platforms.
• Drive cross-team ML engineering standards and governance across the org.
• Tackle ambiguous problems, structure work, and lead execution across engineers.
• Mentor senior engineers and raise production-readiness expectations.
• Lead experimentation at scale, including multi-armed bandits and causal inference.
• Foster culture through design reviews, documentation and RFCs.

Skills

ML Architecture

Technical Leadership

ML Mastery

Production ML Engineering

Software Engineering

Strategic Thinking

Payments Domain

Cloud Infrastructure

Job description

At PPRO, we simplify access to local payments - providing a local payments platform that empowers giants like PayPal, Stripe, and Microsoft to connect with billions of consumers worldwide. We are on an ambitious, fast-paced mission to 3x our growth by 2028 - and we’re just getting started.
Our magic lies in our team of proud payments nerds. Spanning over 50 nationalities across 10+ global locations, our diverse cultures aren't a checklist; they are the competitive advantage driving our innovation. This is a people-first, high trust environment where you’ll have the autonomy to make a massive impact, own your work end-to-end, and grow through broad exposure, meaningful challenges, and continuous learning. We get things done, challenge respectfully, put the customer first, and recognise that our biggest successes are those we create as a team. If you’re ready to leave your footprint on global commerce, join us.

The Purpose:

As a Staff Machine Learning Engineer in PPRO's Performance Powerhouse team, you will define the technical vision and architecture for ML-driven payment optimization across the organization. You will move beyond executing well-defined problems to identifying and framing the highest-leverage opportunities—bridging strategy, architecture, and execution across multiple teams. You'll partner deeply with Product, Data, Core Payments, and Platform Engineering to set standards, eliminate systemic bottlenecks, and ensure PPRO's ML capabilities scale with the business.
This role is for engineers who have mastered ML and software craft at the senior level and are now ready to multiply their impact through technical leadership, mentorship of senior engineers, and architectural decisions that shape how the Data & ML organization builds and deploys ML systems. You will be the technical authority on ML for payments at PPRO—setting the direction others follow, raising the bar across the discipline, and driving alignment across engineering, product, and data teams.

Your impact in this role:

• Define ML Technical Strategy: Drive the multi-quarter roadmap for ML-driven authorization optimization, routing intelligence, and retry strategies. Identify the highest-impact opportunities before they become obvious, and build the case for investment with data and business framing.
  

• Architect Foundational ML Systems: Design and lead the implementation of shared ML infrastructure—feature stores, model serving platforms, experimentation frameworks that accelerates every team building on payments data, not just your own.
  

• Drive Cross-Team Technical Standards: Author and champion ML engineering standards across PPRO (model governance, monitoring, MLOps patterns), ensuring consistency, reliability, and reproducibility organization-wide.
  

• Solve Ambiguous, High-Stakes Problems: Take on challenges where the problem itself isn't well-defined. You scope, structure, and sequence the work—then lead execution across multiple engineers and teams to deliver.
  

• Mentor and Level Up Senior Engineers: Actively invest in the growth of Senior engineers: through design reviews, pairing on hard problems, sponsoring stretch opportunities, and raising expectations for what "production-ready ML" means at PPRO.
  

• Lead Experimentation at Scale: Design the experimentation strategy for live payment traffic—including multi-armed bandits, causal inference approaches, and traffic-splitting frameworks—ensuring sound statistical methodology across the team.
  

• Elevate Engineering Culture: Run design reviews, set expectations for technical documentation, and create the internal forums (guilds, working groups, RFCs) that help ML practitioners across teams learn from each other and align on standards.
  

What would make you a great fit:

• ML Architecture at Scale: Demonstrated experience designing and shipping ML systems that serve multiple products or teams— not just models, but the platforms, contracts, and abstractions that make ML reusable and reliable at scale.
  

• Technical Leadership Without Authority: Proven ability to drive technical decisions across teams you don't manage—through clear writing, credibility, and the ability to synthesize competing perspectives into a coherent path forward.

• Deep Classical & Applied ML Mastery: Expert-level command of classical ML (XGBoost, LightGBM, calibration, cost-sensitive learning) with the judgment to know when—and when not—to reach for more complex approaches. You've operated beyond standard accuracy metrics and can design evaluation frameworks appropriate to the problem.
  

• Production ML Engineering: Extensive experience taking models from experimentation to high-throughput, low-latency production environments. You've owned reliability, SLAs, and incident response for ML systems, and you've built MLOps tooling—not just consumed it.
  

• Software Engineering Excellence: You write and review code at a senior+ level in Python, hold the team to high standards for testability and maintainability, and can credibly engage in systems design discussions with Principal and Staff engineers across Data and Platform.
  

• Strategic Thinking & Business Acumen: You connect technical decisions to business outcomes—approval rate improvements to revenue, latency reductions to conversion, model drift to operational risk. You communicate clearly with non-technical stakeholders and can translate ambiguous business goals into concrete ML problems.
  

• Payments Domain Depth: Strong understanding of the card payment lifecycle, issuer behavior, authorization codes, retry logic, network rules, and 3DS. You use domain knowledge to inform feature design, model architecture, and experimentation strategy—not just as background context.
  

• Cloud Infrastructure Mastery: Deep experience designing and owning ML infrastructure on AWS or GCP at scale, including infrastructure-as-code, cost management, and the ability to make build-vs-buy decisions on platform components.
  

What's in it for you?

• Hybrid working - We offer a hybrid structure with a 3 days / week on site expectation, so you can strike the balance between office and home working. In addition to our 30-day holiday allowance, we also provide a work from abroad policy, enabling employees to work remotely for up to another 30 days per year.

• Learning and Development - We offer a €1,000 annual budget to support your professional growth—because investing in your development benefits us all. In addition, we provide leadership cafés, on-the-job training, and other opportunities to help you grow your skills and thrive in your role.

• Insurance - Because better safe than sorry - we want our employees to benefit from various insurances including accident insurance, disability insurance, direct insurance (bAV) and travel insurance.

• Enhance Family Leave - We understand the importance of family - that's why we offer enhanced family leave to support you during key life moments.

• Gym membership - PPRO helps contribute towards the costs of your gym membership, supporting your physical fitness journey while easing the burden on your wallet.

• Mental Health Platform - We’ve teamed up with a top well-being platform to provide one-on-one therapy, chat therapy, therapist-led courses, guided meditations, and more.

• Our office - Located on St.-Martin-Straße, one stop from Ostbahnhof on the 3 and 7 S-lines. The office is situated in a modern and spacious building with fully multimedia-equipped meeting rooms for up to 30 people. The 4th floor features a kitchen and a lunch area, providing a comfortable space for meals and breaks.

• Pet-friendly office - Because work is better with your paw-tners by your side.

Our Principles:

We get things done: We are courageous; we take ownership, make decisions and get things done.

We act with trust and integrity: We listen first and challenge respectfully. We seek out and leverage diverse perspectives. We welcome and offer honest and open feedback, always assuming positive intent

We put the customer first: We are laser focused on delivering outstanding outcomes for our customers. We put the customer at the heart of what we do.

We make things better: We boldly explore new ideas and have an unwavering commitment to continuous improvement.

We work as a team: We collaborate closely and value team success over individual achievement.

Our commitment to Diversity and Inclusion:

Payments only work when they reflect how different people actually pay, and we build teams the same way: our people span more than 50 nationalities, and that mix is exactly what makes us good at this. So if you're reading this and wondering whether you tick every box, apply anyway. We're far more interested in what you'll bring than a perfect match on paper.

We welcome applicants of every background, identity, and experience, and we make sure our hiring process is accessible to everyone. If you need an adjustment at any stage, just let us know: we're happy to help.

A few more things:

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please refer to our Candidate Privacy Policy.