Job Overview

Job Type

Full Time

Pay

Not disclosed

Apply Now

Job description

How the DADOS team builds Loft

Our team's main missions are to ensure that Loft makes the best data-based decisions and extract maximum value from Machine Learning and AI to generate business solutions. Furthermore, we are responsible for creating tools and technologies that democratize access to information, allowing everyone in the company to use data efficiently. Our daily routine involves building data products, monitoring experiments, projections and analytical studies, always focused on optimizing business results. We are looking for people who are driven by challenges, enjoy working as a team and want to develop in a dynamic environment. We believe in a diverse team, aligned with our purpose and with a high-performance mentality to build, together, the largest real estate ecosystem in Latin America.

The challenges you will encounter

Develop innovative products based on foundation models and machine learning

Monitor the impact of data solutions, transforming technical metrics into strategic insights for senior leadership.

Act consultatively with stakeholders to identify opportunities, design new solutions or optimize legacy products.

Collaborate in multidisciplinary squads, integrating Product, Design and Engineering views to enable the implementation of these solutions.

Ensure continuous evolution and proactive maintenance of the existing product ecosystem.

What do you need to turn the key?

Technical Mastery: Solid knowledge in Statistics and Machine Learning (required)

Tooling and Engineering: Proficiency in Python and SQL, practical experience in code versioning (Git) and practical experience with foundationmodels APIs

Culture and Collaboration: Experience in multidisciplinary squads and have a collaborative profile, with a focus on sharing knowledge and autonomy.

Communication and Interface: Ability to translate complex technical concepts for business leaders and stakeholders.

Soft Skills: Proactive stance, analytical profile and focus on execution (hands-on).

Differential: Experience with the complete deployment cycle and monitoring of models in production; Experience with RAG and LLM development frameworks; Experience with monitoring the performance and cost of foundation models.