Machine Learning Engineer

As a Machine Learning Engineer, your mission is to design and deploy intelligent systems that power core product experiences. You'll transform rich data into models that drive automation, personalization, and smart decision-making at scale. This role blends engineering and applied science, focused on building robust, adaptive ML systems that evolve continuously and make a tangible impact.

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.

Diversity and inclusion:

We believe in social inclusion, respect, and appreciation of all people. We promote a welcoming work environment, where each CloudWalker can be authentic, regardless of gender, ethnicity, race, religion, sexuality, mobility, disability, or education.