Top Machine Learning Jobs in Brazil

The intern will develop AI models, enhance neural mechanism understanding, and collaborate on generative modeling while maintaining code quality.

Develop and evaluate scalable deep learning algorithms, collaborate on generative modeling, and improve data processing pipelines to enhance understanding of neural mechanisms.

The Machine Learning Engineer collaborates to design, deploy, and maintain ML models for medical imaging, ensuring production readiness and optimization.

The role involves developing AI solutions for pre-silicon verification processes, collaborating with teams to enhance methodologies, and engaging with clients to deliver innovative strategies.

Architect, build, and deploy low-latency, high-throughput ML systems across the full ML lifecycle: scalable feature pipelines, training/tuning of tree and deep models, production packaging/serving, MLOps automation, monitoring for drift, and rigorous A/B experimentation to drive business metrics.

As a Machine Learning Engineer/Data Scientist, you'll build and deploy ML solutions, collaborate with stakeholders, and analyze data, focusing on achieving measurable business impact.

As a Senior AI/ML Engineer, you will design and implement AI solutions, collaborate with cross-functional teams, and ensure robust deployment in healthcare contexts.

The Senior Machine Learning Engineer at AB InBev will design and implement ML systems and pipelines to drive AI's mission for the Growth Group.

As a Mid-Level Machine Learning Engineer, you will deploy and maintain ML models, design APIs, and improve model performance, handling real-time data integration.

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

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.

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.

Design and implement AI applications, collaborate with teams, deploy AI models, and improve solutions in production environments.

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

The ML Manager for the AI Platform will lead a team of Machine Learning Engineers, oversee strategic planning, architecture, and execution of AI solutions, focusing on MLOps and Infrastructure to enhance the ML lifecycle.

The Senior Machine Learning Engineer designs and maintains ML solutions, collaborates on data-driven projects, and mentors junior engineers.

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