Machine Learning Engineer
São Paulo
CloudWalk
Our mission is to create the best payment network on Earth. Then other planets.About the Role:
- You’ll join our AI team, focused on ambitious, high-impact projects beyond day-to-day urgencies.
- Work across a spectrum of machine learning solutions—from traditional ML models to agentic systems.
- Collaborate closely with a distributed, cross-functional team of Engineers, Data Scientists, and Analysts in a culture that values open discussion, intellectual honesty, and creative problem-solving.
- Experiment with emerging techniques and architectures to push the boundaries of real-world AI capabilities.
- Working remotely, autonomy is essential—but so is communication and a shared commitment to building meaningful, intelligent systems.
- We look for people with the curiosity of a researcher, the mindset of a builder, and the maturity to own both problems and outcomes.
About CloudWalk:
- CloudWalk is an AI-first fintech building its own technology to bring justice to the broken payment system in Brazil.
- Some people say a company is a unicorn when it reaches a valuation of over 1 billion dollars. We are one of those companies, and that's nice, but not the most important thing.
- We work in the finance sector, a very traditional niche, but we try to do things differently.
The AI team:
- We love data and technology—and you’ll have plenty of both to work with.
- We enjoy simple solutions that work, no overcomplication.
- We are a multidisciplinary team with backgrounds that includes engineering, physics, architecture and more.
- The projects we work on are as diverse as our backgrounds: Credit Models, LLMs agents, Growth, Products and so on.
- We value exploration before exploitation—curiosity comes first.
What you'll do:
- Design, build, and maintain scalable and reliable machine learning infrastructure.
- Deploy and monitor machine learning models for real-time inference.
- Develop and maintain robust REST APIs for our machine learning services.
- Collaborate with data scientists to productionalize their models and algorithms.
- Write clean, maintainable, and well-tested production code.
- Optimize and improve the performance of our machine learning systems.
- Stay up-to-date with the latest technologies and best practices in machine learning and MLOps.
What you'll need:
- Initiative to learn, investigate, experiment.
- Ability to communicate and debate in English and Portuguese.
- Excellent problem-solving and communication skills.
- Strong programming skills in Python and experience with common data science libraries (e.g., pandas, scikit-learn).
- Experience in building and deploying REST APIs using frameworks like Flask, FastAPI, or Django.
- Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
- Solid understanding of software engineering best practices, including version control (Git), testing, and CI/CD.
- Experience with cloud platforms such as AWS or Google Cloud.
Bonus points if you have:
- Experience with MLOps tools and platforms (e.g. MLflow).
- Experience with real-time data processing frameworks (e.g. Kafka).
- Experience as a Machine Learning Engineer, Data Scientist, Data Engineer, or in a similar role.
- Experience with deep learning frameworks like PyTorch.
- Great SQL skills.
- Agentic frameworks like LangChain.
Recruiting process outline:
- Online assessment: an online test to evaluate your theoretical skills and logical reasoning.
- Case: a technical project where you'll deploy a machine learning model for real-time inference.
- Technical interview and case presentation.
- Cultural interview. If you are not willing to take an online quiz and work on a test case, do not apply.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Architecture AWS CI/CD Deep Learning Django Docker Engineering FastAPI Finance FinTech Flask GCP Git Google Cloud Kafka Kubernetes LangChain LLMs Machine Learning MLFlow ML infrastructure ML models MLOps Pandas Physics Python PyTorch Scikit-learn SQL Testing
Perks/benefits: Career development Startup environment
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