Top Machine Learning Jobs in Sao Paulo

Design, develop, and deploy machine learning pipelines. Implement MLOps practices and optimize models. Collaborate on data pipelines and cloud deployment.

Design, build, evaluate, and deploy production-grade LLM and classical ML solutions. Create retrieval and agentic workflows, integrate AI into client apps, implement evaluation frameworks, optimize prompts and pipelines, and collaborate with product teams through discovery to production support.

Own the architecture, development, automation, and production deployment of end-to-end machine learning solutions. Manage the ML lifecycle, evaluate cloud architectures for performance and cost efficiency, integrate with data engineering and software teams, troubleshoot complex systems, align solutions with business needs, and mentor teams on MLOps adoption.

Design, build, and deploy ML models and end-to-end pipelines; collaborate with data and MLOps teams to integrate, monitor, retrain, and optimize models; implement cloud-based scalable solutions and document processes.

Build, deploy, and maintain production-grade ML models and data pipelines in cloud environments. Perform EDA and feature engineering, monitor model performance and drift, and collaborate with engineering and business stakeholders. Contribute to AI/LLM initiatives and ensure solutions operate reliably in production.

The Data Scientist will lead data-driven decision-making, develop machine learning models, design automated pipelines, and improve product performance.

Design, build, and deliver enterprise-grade Generative AI/ML platform services, reusable frameworks, APIs, and agentic applications. Implement scalable model deployment, inference, monitoring, CI/CD, event-driven streaming (Kafka), and secure microservices while collaborating with architects, data scientists, and stakeholders to ensure governance, scalability, and operational excellence.

The AI/ML Engineering Manager will lead a team of ML engineers, manage client engagements, shape architecture, and drive pre-sales while ensuring team growth and performance.

Develop and implement LLM workflows, collaborate with teams on AI/ML solutions, ensure quality delivery using CI/CD practices, and support technical duties.