Staff Machine Learning Engineer

PPRO

Staff Machine Learning Engineer at PPRO defining technical vision and architecture for ML-driven payment optimization. Leading technical strategy, mentoring, and collaboration across teams in fintech.

Posted 7/3/2026full-timeSao Paulo • 🇧🇷 BrazilLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and delivering scalable ML systems, with a strong focus on production ML engineering and cloud infrastructure mastery. Proven ability to lead technical strategy and influence cross-team decisions while connecting technical outcomes to business objectives.

Highest-signal resume keywords

ML Architecture At ScaleDeep Classical & Applied ML MasteryProduction ML EngineeringSoftware Engineering ExcellencePayments Domain Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningML Systems DesignPython ProgrammingCloud InfrastructureTechnical StrategyExperimentationCode ReviewClassical Machine Learning TechniquesApplied Machine LearningTechnical Standards

Soft Skills

Technical LeadershipStrategic ThinkingMentoringInfluencing Without AuthorityProblem Solving

Tools & Technologies

AWSGCP

Industry Keywords

Payments DomainCard Payment Lifecycle

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Define the ML technical strategy for ML-driven authorization optimization.
Architect foundational ML systems to accelerate every team building on payments data.
Drive cross-team technical standards across PPRO.
Solve ambiguous, high-stakes problems by leading execution across multiple engineers and teams.
Mentor and level up senior engineers through design reviews and by sponsoring stretch opportunities.
Lead experimentation at scale with live payment traffic.
Elevate engineering culture by creating internal forums for ML practitioners to learn from each other.

Requirements

What you’ll need

ML architecture at scale: Demonstrated experience designing and delivering ML systems that serve multiple products or teams.
Technical leadership without authority: Proven ability to influence and drive technical decisions across teams you don't manage.
Deep classical & applied ML mastery: Expert-level command of classical machine learning techniques.
Production ML engineering: Extensive experience taking models from experimentation into production environments.
Software engineering excellence: Ability to write and review code at a senior+ level in Python.
Strategic thinking & business acumen: Track record of connecting technical decisions to business outcomes.
Payments domain expertise: Strong understanding of the card payment lifecycle.
Cloud infrastructure mastery: Deep experience designing and owning ML infrastructure on AWS or GCP at scale.

Benefits

Comp & perks

Hybrid working – We offer a hybrid structure with a 3 days / week on-site expectation, allowing you to balance office and remote work.
30-day holiday allowance.
Work-from-abroad policy enabling employees to work remotely for up to an additional 30 days per year.
BRL 3,000 annual budget to support your professional growth.
Leadership cafés, on-the-job training, and other opportunities to help you grow your skills and thrive in your role.
Life insurance.
Health insurance and dental plan.
Travel insurance.
Meal vouchers – BRL 54/day.
Enhanced family leave.
Transportation voucher.
Gym membership.
Pet-friendly office.