Job
- Level
- Senior
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Job Field
- Software, Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
Job Summary
In this role, you will define the technical vision for ML-driven payment optimization, develop ML architectures, lead experiments, and establish standards to enhance ML capabilities across the organization.
Job Technologies
Your role in the team
- 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.
- 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.
- 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.
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Our expectations of you
Qualifications
- 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.
- 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.
Experience
- ML architecture at scale: Proven experience in designing and deploying ML systems that support multiple products or teams — not just models, but also the platforms, contracts, and abstractions that enable ML to be reusable and reliable at scale.
- Production ML Engineering: Extensive experience taking models from experimentation to high-throughput, low-latency production environments.
- Mastery of Cloud Infrastructure: Extensive experience in designing and managing 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.
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What we offer
- 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 it's better to be safe than sorry - we want our employees to benefit from various insurances including accident insurance, disability insurance, direct insurance (bAV), and travel insurance.
- Gym membership - PPRO helps contribute towards the costs of your gym membership, supporting your physical fitness journey while easing the burden on your wallet.
- Enhance Family Leave - We understand the importance of family - that's why we offer enhanced family leave to support you during key life moments.
- 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.
- Pet-friendly office - Because work is better with your paw-tners by your side.
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Benefits
Health, Fitness & Fun
Food & Drink
Topics You Will Work On
Job Locations
About Your Employer
PPRO Group
At PPRO, we're passionate about payments and dedicated to making sure people can pay and get paid. Over the past 10 years, we've built a leading payments infrastructure from our offices in London, Munich, Luxembourg, Cologne, Atlanta, and Singapore. As a company, we're constantly evolving and striving to provide the best possible experience for our customers.
Description
- Founding Year
- 2006
- Language
- English
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Internet, IT, Telecommunication
Staff Machine Learning Engineer
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
