CI&T
[Job-31614] Senior Machine Learning Engineer, Brazil
Remote role where the employee must remain based in a particular country.
Brazil only
Employer listed it 9 days ago · Added today
First listed 9 days ago and still open.
Salary
Not stated
Location
Brazil only
Timezone
Not stated
Contract
Full-time
Experience
Senior
Category
Data
This employer didn't state pay. Jobs like this usually pay around $135k–$210k a year, a typical range taken from 260 senior-level data roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Work from home
This is a remote role, but the employee must be based in Brazil. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "Brazil, remote"
What Nomaders makes of it
- Residency required in Brazil
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
About the Opportunity
We are looking for a Senior Machine Learning Engineer to lead the development, industrialization, and evolution of Machine Learning products at an enterprise scale.
This professional will work at the intersection of Data Science, Data Engineering, and MLOps , taking ownership of the architecture, governance, operationalization, and support of ML solutions in production. The role requires end-to-end ownership, from solution design and development to monitoring, documentation, and continuous improvement.
Key Responsibilities
Lead MLOps initiatives , including model training, deployment, model serving, monitoring, and lifecycle governance.
Develop and maintain ETL/ELT pipelines, DAGs, and data and Machine Learning workflows using PySpark.
Design and manage enterprise Feature Stores , ensuring feature versioning, lineage, and consistency between training and inference.
Develop, validate, and operationalize Machine Learning models for different analytical use cases.
Implement model versioning strategies, Champion/Challenger approaches, rollouts, model promotion, and Model Registry management .
Ensure observability, quality, traceability, reproducibility, and governance across data, features, pipelines, and models.
Design and implement CI/CD processes and Infrastructure as Code (IaC) for Machine Learning platforms.
Define architectural standards, engineering best practices, and MLOps guidelines.
Conduct technical code reviews, support Data Scientists in industrializing ML solutions, and maintain technical, architectural, and operational documentation.
Required Qualifications
Advanced experience with Databricks , including MLflow, Unity Catalog, Delta Lake, Databricks Workflows, Model Registry, Model Serving, and Databricks Asset Bundles (DABs) .
Strong experience developing, operationalizing, and monitoring Machine Learning models in production .
Experience with Feature Engineering, hyperparameter optimization, model evaluation, and supervised and unsupervised learning algorithms .
Experience with enterprise Feature Stores , including feature versioning and point-in-time lookups.
Knowledge of Data Drift, Concept Drift, Performance Drift , and observability of data and ML pipelines.
Experience building CI/CD pipelines , managing DEV, QA, and PROD environments, and implementing Infrastructure as Code.
Experience with automated testing for data and Machine Learning pipelines.
Requirements
- ·Advanced experience with Databricks , including MLflow, Unity Catalog, Delta Lake, Databricks Workflows, Model Registry, Model Serving, and Databricks Asset Bundles (DABs) .
- ·Strong experience developing, operationalizing, and monitoring Machine Learning models in production .
- ·Experience with Feature Engineering, hyperparameter optimization, model evaluation, and supervised and unsupervised learning algorithms .
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at CI&T, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 14h ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
Similar roles
Other open data roles with comparable remote rules.
Free to apply, no account needed.
Typically $135k to $210k per year · You'll be taken to the employer's careers page.