This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data & Machine Learning Engineer based in Brazil.

In this role, you will help design and evolve end-to-end data and ML infrastructure powering large-scale analytics, intelligent search, and LLM-driven applications. You will work across data engineering and machine learning operations, building pipelines that support both traditional BI and modern AI use cases. The environment is highly technical and global, with strong emphasis on scalability, performance, and innovation. You will contribute to architectures involving data lakes, feature stores, vector databases, and real-time processing systems. This is a hands-on role where you will collaborate closely with BI, engineering, and product stakeholders. The work directly impacts data-driven decision-making and next-generation AI capabilities across business operations.

In this role, you will design, build, and maintain scalable data and ML pipelines that support ingestion, transformation, storage, and delivery for analytics and AI systems. You will contribute to the development of LLM-powered solutions and retrieval-based architectures, ensuring data is structured and accessible for model training and inference.

• Design and maintain scalable data pipelines for batch and real-time processing, supporting feature stores, ML workflows, and inference systems
• Build and optimize workflows for structured and unstructured data, enabling semantic search and retrieval-augmented generation (RAG) use cases
• Develop and support ML and LLM-based data solutions, including orchestration, prompt workflows, and model fine-tuning processes
• Manage and optimize vector databases and indexing strategies for efficient retrieval and AI-powered search
• Collaborate with stakeholders to translate business requirements into scalable data and ML solutions
• Maintain documentation for data pipelines, model workflows, and deployment processes
• Stay updated with emerging trends in data engineering, MLOps, and LLM technologies

Requirements

The ideal candidate brings strong experience in data engineering combined with exposure to MLOps and modern AI/LLM ecosystems. You should be comfortable working in distributed environments, building robust pipelines, and integrating machine learning systems into production workflows.

• 8+ years of experience in Data Engineering, including at least 2+ years in MLOps or ML-focused environments
• Strong proficiency in Python for data processing, transformation, and large-scale pipelines
• Deep understanding of data architecture, BI systems, and data warehousing concepts (SQL, PL/SQL, Snowflake, Redshift or similar)
• Hands-on experience with big data tools such as Spark, Kafka, and Hadoop
• Experience working with vector databases and RAG-based architectures
• Familiarity with LLM frameworks and integration into data pipelines for training, inference, and orchestration
• Experience with cloud platforms such as AWS or Azure ML environments
• Strong understanding of ETL processes and data ingestion from multiple sources (APIs, RDBMS, files, JSON)
• Experience working in Agile environments and using version control systems (Git workflows)
• Excellent English communication skills and ability to collaborate with global teams

Benefits

• Competitive compensation aligned with international market standards
• Fully remote work within LATAM
• Opportunity to work on cutting-edge AI, LLM, and data engineering projects
• Exposure to large-scale, global data environments and modern cloud architectures
• Collaborative and international team environment
• Career growth in advanced analytics, MLOps, and AI engineering domains
• Participation in high-impact projects shaping data-driven decision-making

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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