Time since we first saw it
Day 204
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Machine Learning Engineering Specialist
Curitiba | On-site
Open 6 months, first seen by us 204 days ago- Pay
- Pay not listed
- Work setting
On-site — work setting source
Listed location: Curitiba | On-site
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingDesign the system architecture to train, deploy, monitor, and serve ML models in production
Build and maintain scalable infrastructure for ML pipelines, APIs, and ML products
Implement and manage CI/CD pipelines for deploying and monitoring ML models and services
Ensure security and privacy compliance, especially in the financial context
Troubleshoot and optimize ML production systems for performance and reliability
From the employer’s posting
Responsible for designing the system architecture to train, retrain, develop, monitor, deploy, and serve machine learning models in production;
Design, develop, and maintain scalable infrastructure to support machine learning pipelines, APIs, and ML products;
Implement and manage CI/CD pipelines for the deployment, updating, and continuous monitoring of machine learning models and services;
Ensure compliance with security and privacy requirements, especially in the financial context;
Troubleshoot and optimize machine learning production systems, ensuring performance, reliability, scalability, and operational stability;
Posting record
Report an errorOpen 6 monthsWe first saw this posting 204 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 14, 2026204 days ago
- Recorded sightings
- 145
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EBANX is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
- 33% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Azure
- Datadog
- Docker
- GCP
- Grafana
- Kafka
- Kubernetes
- Terraform
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and the infrastructure and production requirements of ML models; - Strong Python skills with experience writing clean, efficient, and maintainable code; - Experience with CI/CD tools such as GitLab CI, Jenkins, or GitHub Actions, as well as infrastructure as code tools such as Terraform;
- Hands-on experience as a Machine Learning Engineer, MLOps Engineer, or in related roles, with solid practical experience building and supporting infrastructure for machine learning models in production; - Strong experience with cloud platforms such as AWS, GCP, or Azure; - Proficiency with containerization tools such as Docker and orchestration systems (e.g., Kubernetes);
- Knowledge of data pipelines and ETL processes (streaming and batch); - Experience with monitoring, logging, and alerting solutions for machine learning services (e.g., Prometheus, Grafana, Datadog); - Understanding of security and compliance standards in payment systems.
- Strong experience with cloud platforms such as AWS, GCP, or Azure; - Proficiency with containerization tools such as Docker and orchestration systems (e.g., Kubernetes); - Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and the infrastructure and production requirements of ML models;
Bonus points if you have: - Knowledge of Kafka or similar event streaming platforms; - Familiarity with financial services or payment systems;
- Strong Python skills with experience writing clean, efficient, and maintainable code; - Experience with CI/CD tools such as GitLab CI, Jenkins, or GitHub Actions, as well as infrastructure as code tools such as Terraform; - Knowledge of data pipelines and ETL processes (streaming and batch);
- Proficiency with containerization tools such as Docker and orchestration systems (e.g., Kubernetes); - Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and the infrastructure and production requirements of ML models; - Strong Python skills with experience writing clean, efficient, and maintainable code;
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
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Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
EBANX is one of the most successful fintechs to emerge from Latin America — and today, we are building a truly global payments company. Our mission has remained constant from day one: to unlock access and enable companies and consumers to participate in the digital economy, no matter where they are.
What started as a bold vision has grown into a platform that connects some of the world’s largest digital businesses with customers across 21 of the fastest-growing markets. We operate where complexity exists — turning local challenges into global opportunities, and building the infrastructure that allows payments to move further, faster, and smarter.
We are a team of builders and problem-solvers. We think globally, act with curiosity, and believe diversity of thought is a competitive advantage.
As EBANX enters its next phase of hyper growth, we are looking for people who want to shape the future of payments, expand what’s possible, and help connect businesses and consumers across borders.
Let’s build what’s next — together.
At EBANX’s Data team you don’t just work with numbers. You transform information into intelligence that drives strategic decisions and directly impacts the digital payments revolution on a global scale. Every analysis combines curiosity, rigor, and collaboration, making our work truly Out of the Ordinary.
• As an AI Engineer Specialist your mission will be to own the design and deployment of scalable AI systems in production.
Your day-to-day impact:
- Responsible for designing the system architecture to train, retrain, develop, monitor, deploy, and serve machine learning models in production;
- Design, develop, and maintain scalable infrastructure to support machine learning pipelines, APIs, and ML products;
- Implement and manage CI/CD pipelines for the deployment, updating, and continuous monitoring of machine learning models and services;
- Work with infrastructure and engineering practices specifically designed for machine learning products, including deployment, APIs, automation, and infrastructure as code;
- Collaborate closely with data scientists, software engineers, and cross-functional teams to ensure seamless integration of machine learning models into production;
- Ensure compliance with security and privacy requirements, especially in the financial context;
- Troubleshoot and optimize machine learning production systems, ensuring performance, reliability, scalability, and operational stability;
- Share knowledge, mentor, and support team members in MLOps best practices, API development, and machine learning model production.
Must-haves to shine in this role:
- Hands-on experience as a Machine Learning Engineer, MLOps Engineer, or in related roles, with solid practical experience building and supporting infrastructure for machine learning models in production;
- Strong experience with cloud platforms such as AWS, GCP, or Azure;
- Proficiency with containerization tools such as Docker and orchestration systems (e.g., Kubernetes);
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and the infrastructure and production requirements of ML models;
- Strong Python skills with experience writing clean, efficient, and maintainable code;
- Experience with CI/CD tools such as GitLab CI, Jenkins, or GitHub Actions, as well as infrastructure as code tools such as Terraform;
- Knowledge of data pipelines and ETL processes (streaming and batch);
- Experience with monitoring, logging, and alerting solutions for machine learning services (e.g., Prometheus, Grafana, Datadog);
- Understanding of security and compliance standards in payment systems.
- Conversational English skills, with the ability to communicate effectively with international stakeholders, participate in discussions, and occasionally present or speak in English.
Bonus points if you have:
- Knowledge of Kafka or similar event streaming platforms;
- Familiarity with financial services or payment systems;
- Experience working with products that use machine learning or AI in their core;
- Experience with risk-related products, transaction routing, fraud prevention, or other payment use cases.
EBANX offers:
- Performance Bonus: Annual bonus program based on company results.
- Meal Allowance: Monthly allowance to support your meals.
- EBANX Education: Financial assistance for undergraduate, graduate, and MBA programs to support your professional growth.
- EBANX Skills: Dedicated budget for courses, certifications, and workshops to encourage continuous learning.
- Language Classes: Language classes to support your personal and professional development.
- Health & Well-being: Medical and dental plans with extensive coverage, including support for dependents and wellness programs.
Flexible Work Culture: Semi-flexible hours, additional day off on your birthday, and year-end break to support work-life balance. - Well-being Program: Access to activities and resources that promote physical and mental health.
Learn more about our #ebanxlife on LinkedIn and Instagram, and see what it’s like to be part of a global team that breaks barriers, creates opportunities, and celebrates every achievement together.
✨ An Out Of The Ordinary career is waiting for you here!
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Curitiba | On-site
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