Data Scientist, Mid-level

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Take charge of the complete end-to-end lifecycle of Artificial Intelligence solutions, encompassing design and architecture through to validation, deployment, and accessibility via APIs, while ensuring scalability, stability, and high performance;

• Create, assess, and refine Machine Learning models and Generative AI applications, guaranteeing the technical quality of solutions and their alignment with business requirements;

• Continuously evaluate the balance between computational expenses and solution performance, taking into account factors such as token usage, inference duration, infrastructure utilization, and return on investment (ROI), and suggest alternatives that enhance efficiency and value for the organization;

• Establish governance, security, and reliability protocols for AI applications, employing strategies such as guardrails, response validation, quality monitoring, and context-anchoring techniques, including Retrieval-Augmented Generation (RAG), to ensure precise, safe, and business-aligned outcomes;

• Design and sustain data pipelines and inference workflows in partnership with multidisciplinary teams, ensuring integration, observability, and ongoing monitoring of models in production;

• Document architectures, models, experiments, and processes to foster traceability, reproducibility, and compliance with data and AI governance standards;

• Work collaboratively with business and technology stakeholders to pinpoint opportunities for AI application, translating complex challenges into scalable, high-impact analytical solutions;

• Remain informed about the latest developments in technologies, frameworks, and best practices related to Data Science, Machine Learning, and Generative AI, proposing innovations that contribute value to the business;

⛳️ Requirements

• Education: Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, Statistics, Mathematics, Physics, or related disciplines.

• A postgraduate degree or specialization in Data Science, Artificial Intelligence, Machine Learning, or related fields will be viewed favorably.

• Profound knowledge of Python and libraries used for data analysis and Machine Learning.

• Experience with AI and Deep Learning frameworks such as PyTorch, TensorFlow, and LangChain.

• Proven track record in developing applications utilizing Large Language Models (LLMs), including both proprietary and open-source models.

• Experience in implementing architectures based on Retrieval-Augmented Generation (RAG), AI agents, multimodal pipelines, and prompt engineering techniques.

• Familiarity with embedding strategies, vector databases, semantic information retrieval, and fine-tuning techniques for open-source models.

• Experience in building, deploying, and maintaining AI applications in production environments, adhering to Software Engineering best practices, including SOLID principles, Design Patterns, version control, and automated testing.

• Knowledge of MLOps, encompassing model versioning, pipeline automation, continuous integration and delivery (CI/CD), monitoring, and model governance.

• Experience with observability for AI applications, implementing metrics, telemetry, and monitoring to identify performance degradation, data drift, model drift, and other key indicators of production health.

• Familiarity with safe model evolution strategies utilizing methods such as Shadow Testing, Shadow Deployment, Canary Releases, and A/B testing to validate new versions in production.

• Experience in developing and consuming REST APIs to expose models and AI services.

• Understanding of relational and non-relational databases, along with tools for processing and managing large volumes of data.

🏝️ Benefits

• Meal voucher (VR)

• Remote work allowance

• Medical insurance (co-payment)

• Bar Association membership (OAB)

• Childcare assistance