Artificial Intelligence Software Developer

Há 3 dias


Ituiutaba, Brasil Bebeeartificialintelligence Tempo inteiro

Job DescriptionWe are seeking a talented Artificial Intelligence Software Developer to join our team.As an AI software developer, you will be responsible for designing, developing, and deploying scalable, production-ready machine learning systems and end-to-end pipelines on cloud-based infrastructure.This is a full-time opportunity where you will be working as part of a collaborative team which requires working closely with other software engineers, stakeholders, and contributors on the project.Required Skills and QualificationsDesign and Development: Design, develop, and deploy scalable, production-ready machine learning systems and end-to-end pipelines on AWS.Collaboration: Partner with data scientists, software engineers, and product teams to define requirements, select algorithms, and deliver impactful ML solutions.Infrastructure Management: Architect, optimize, and maintain ML infrastructure — including data ingestion, model training, deployment, serving, monitoring, and lifecycle management — using AWS services.Data Preparation: Lead the data preparation and feature engineering process, ensuring data quality, integrity, and scalability across large datasets.Model Implementation: Implement and optimize ML models (supervised, unsupervised, deep learning, NLP, recommendation systems) with a focus on performance, accuracy, and reliability.Pipeline Management: Build and manage robust data pipelines and orchestration workflows to support ML systems at scale.BenefitsThis role offers a stimulating and rewarding environment for our team members.We value innovation, continuous learning, and professional growth, and we strive to create a workplace where everyone can thrive.OthersYou will have the opportunity to stay ahead of emerging trends in AI/ML, evaluating new research, frameworks, and tools to enhance product capabilities.You will also provide technical leadership and mentorship to junior engineers, guiding best practices throughout the ML lifecycle.



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