Machine Learning Architect

Mindera

Machine Learning Architect leading design and implementation of scalable AI/ML solutions in Brazil. Collaborating with multiple teams to enable enterprise-scale machine learning capabilities.

Posted 5/13/2026full-timeRemote • 🇧🇷 BrazilSeniorLeadWebsite

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudETLGoogle Cloud PlatformPythonSparkSQLUnity

About the role

Key responsibilities & impact

Define and lead the architecture for scalable Machine Learning and AI platforms.
Design end-to-end ML workflows using Databricks, including: Feature engineering, Model training, Experimentation, Deployment, Monitoring
Architect scalable data pipelines for AI/ML workloads using: Apache Spark, Python, SQL
Establish MLOps best practices including: CI/CD for ML, Model versioning, Model governance, Automated retraining, Model drifting, Observability and monitoring
Design secure and compliant AI architectures aligned with governance and privacy standards.
Partner with Data Engineering teams to optimize data models and feature stores.
Guide Data Scientists and ML Engineers on scalable production design patterns.
Evaluate and integrate modern AI capabilities, including (this will be a plus): LLMs, Vector databases, Retrieval augmented generation (RAG), AI agents
Drive cost optimization, scalability, and operational excellence across ML platforms.
Define reference architectures and best practices across multiple ML teams (not just owning a single project).
Support stakeholder engagement and translate business needs into scalable technical solutions.

Requirements

What you’ll need

8+ years in Data, AI, or Machine Learning Engineering roles.
3+ years designing ML platforms or AI architecture at scale.
Strong hands-on experience with:
- Databricks
- Apache Spark
- Python
- SQL
Strong understanding of:
- MLOps
- ML lifecycle management
- Distributed ML systems
- Feature engineering
- Model deployment patterns
Databricks Unity Catalog, Delta Lake, and Lakehouse architecture experience.
Experience with cloud platforms (AWS, Azure, or GCP).
Experience deploying ML models into production environments.
Strong knowledge of data architecture and scalable ETL/ELT patterns.
Experience working with orchestration frameworks such as Apache Airflow.
Strong stakeholder communication and technical leadership skills.

Benefits

Comp & perks

Work Your Way: Flexibility to choose where you work from (Remote-first culture).
Growth Mindset: Free English lessons and continuous training/learning opportunities.
Well-being First: Access to counseling and psychotherapy services, and incentives in sports competitions, because your mind matters.
Shared Success: Annual profit distribution (subject to company performance and board decision - only for CLT contracts).
The Fun Stuff: Gatherings and annual trip to bond with the team.
Culture of Trust: A collaborative, lean, and self-managed environment where you have the autonomy to make an impact.

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningAI platformsDatabricksApache SparkPythonSQLMLOpsFeature engineeringModel deploymentData architecture

Soft Skills

stakeholder communicationtechnical leadership