Top Machine Learning Jobs in Brazil

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

Lead the architecture and implementation of machine learning solutions, ensuring scalable and secure environments for data teams while collaborating with clients and various stakeholders.

Lead design and implementation of scalable, production-ready AI solutions across products. Automate workflows with AI, build semantic data models and agent-based systems, develop custom LLM skills, apply spec-driven development, define AI integration best practices, and collaborate with product and engineering leadership on AI strategy and adoption.

As an AI/ML Engineer, design and implement AI solutions, collaborate with teams, build ML pipelines, and ensure quality and compliance in healthcare applications.

The role involves architecting and optimizing scalable backend systems for a media intelligence platform, integrating AI/ML workflows for multimedia processing, and overseeing system reliability and performance.

The Principal AI/ML Architect leads client engagements, advising on ML architecture and strategies, overseeing ML systems, and ensuring technical quality for diverse customer needs with a focus on AWS technologies.

Design, build, and maintain scalable data and ML pipelines, manage vector stores and RAG workflows, integrate LLM frameworks for training and inference, enable semantic search and AI-driven BI, and document data processes while partnering with stakeholders.

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.

The Senior AI/ML Engineer will architect and develop AI/ML solutions, collaborate with teams, and ensure deployment compliance, especially in healthcare.

Join the Advanced Accelerator Training Program to master AI/ML skills, engage in real projects, and prepare for impactful roles. Requires 4+ years of ML experience and proficiency in Python and relevant frameworks.

Design, deploy, monitor, and maintain ML models and ML-enabled systems across batch and real-time contexts. Build pipelines, features, tooling and platforms, collaborate with teams, and ensure operational and business performance of ML solutions.

The Engineering Matcher connects clients with technical talent by analyzing resumes, conducting interviews, and maintaining a candidate pool while collaborating with stakeholders.

Seeking a Software Engineer with 5+ years in AI/ML to design and implement scalable web APIs and applications, focusing on generative AI solutions, while engaging cross-functional teams and mentoring junior developers.

Lead Machine Learning Engineer to execute complex AI research, optimize architectures for production use, and mentor team members, focusing on scalable financial solutions.

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

The Machine Learning Engineer will develop RAG models, optimize machine learning systems, collaborate with clients, and lead AI projects for effective solutions.

Own product direction for ML platform capabilities across the end-to-end ML lifecycle. Set vision and roadmap, define standards and tooling, drive adoption with data science and engineering teams, deliver templates/CLIs/workflows, and improve model deployment, observability, and operational practices to enable scalable, reliable ML solutions.

As a Machine Learning Solutions Architect, you will design and implement data solutions, provide thought leadership, and ensure scalable deployment of machine learning models.

Build and maintain production ML infrastructure: deploy, monitor, and scale models; create automated end-to-end pipelines; implement CI/CD for model releases; establish monitoring/logging/alerting; optimize system architecture for reliability, scalability, and cost; collaborate with data scientists and engineers to operationalize models.

Design and implement recommender systems, manage ML pipelines, optimize models, and collaborate with teams to improve customer engagement.

As a Machine Learning Engineer at CloudWalk, you will design, train, and deploy ML models for security, focusing on anomaly detection and protection against attacks in real-time, all while working in a collaborative, fully remote environment.