Pleno Machine Learning Engineer

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities:

The Pleno Machine Learning Engineer will be responsible for designing, developing, and maintaining advanced artificial intelligence solutions, transforming business challenges into scalable and impactful technology products. The role requires strong technical expertise, autonomy, and collaboration across different teams. Key responsibilities include:

• Designing and architecting Intelligent Document Processing (IDP) solutions, developing and optimizing pipelines for extracting information from complex, unstructured documents.
• Building and improving machine learning and Generative AI solutions, including fine-tuning strategies, Retrieval-Augmented Generation (RAG), and computer vision applications.
• Developing and deploying agentic AI workflows using frameworks such as LangGraph, n8n, and similar technologies, ensuring reliability, scalability, and efficient orchestration.
• Creating structured data pipelines and advanced analytical models to transform extracted information into strategic insights, predictive intelligence, and business-oriented products.
• Establishing evaluation frameworks for AI systems, monitoring model performance, reducing hallucinations, improving accuracy, and optimizing infrastructure costs.
• Collaborating with Product Managers, Engineering teams, and technical leadership to translate business needs into effective AI architectures and production-ready solutions.
• Supporting the development of prototypes and proofs of concept through to final implementation in production environments.
• Promoting technical excellence by mentoring junior team members and sharing best practices in software development, modeling, and AI engineering.

Requirements:

The ideal candidate is an experienced Machine Learning professional with a strong background in developing AI solutions for production environments. This role requires advanced programming skills, knowledge of modern AI architectures, and the ability to communicate complex concepts effectively. Required qualifications and skills include:

• Bachelor’s degree completed in Computer Science, Engineering, Statistics, Mathematics, Physics, Data Science, or related quantitative fields.
• Proven experience developing and maintaining Machine Learning and Generative AI models in production environments.
• Advanced proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
• Advanced SQL skills, including query optimization, data modeling, and handling large-scale datasets.
• Strong knowledge of statistics, including descriptive and inferential analysis, multivariate analysis, and hypothesis testing applied to data products.
• Experience with Generative AI technologies, including LLM/SLM fine-tuning, prompt engineering, RAG architectures, and agent-based AI frameworks such as LangGraph, LangChain, or AutoGen.
• Experience with AI evaluation and observability frameworks such as Ragas, TruLens, DeepEval, LangSmith, or similar solutions.
• Knowledge of document processing technologies, OCR, NLP, and computer vision tools such as Google Document AI, AWS Textract, Azure Form Recognizer, Tesseract, or LayoutLM.
• Solid understanding of software architecture principles, REST APIs, microservices, Git, and scalable engineering practices.
• Ability to independently transform complex and ambiguous problems into complete technical solutions.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders and mentor other professionals.

Preferred qualifications include:

• Experience with MLOps practices, cloud platforms such as AWS or GCP, Docker, Kubernetes, and CI/CD pipelines for machine learning.
• Experience optimizing AI infrastructure costs while maintaining or improving model accuracy.
• Knowledge of credit operations, risk analysis, document workflows, real estate documentation, or agribusiness processes.
• Technical portfolio, open-source contributions, published articles, or demonstrated participation in the AI and data community.

Benefits:

• 100% remote work model.
• Full-time employment opportunity.
• Meal and food allowance through a flexible benefits platform.
• Health and dental insurance.
• Life insurance coverage.
• Pet care support benefit.
• Access to psychological support services.
• Wellness benefits, including fitness and health partnerships.
• Learning and professional development opportunities.
• Access to cultural and leisure partnerships.
• Childcare assistance for eligible employees.
• Family support benefit for new parents.
• Birthday day off.
• 44-hour weekly schedule.
• Opportunity to work with innovative AI technologies and impactful products.
• Collaborative environment focused on growth, inclusion, and continuous learning.