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.

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

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.

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.

Design, build, and maintain scalable ML models and data pipelines to automate logistics processes. Own end-to-end projects from problem definition to production deployment and monitoring. Collaborate with engineering, mentor ML teammates, review code, and evaluate tooling to improve infrastructure and workflows that deliver customer value.

Design, build, and deploy agentic LLM workflows that plan, call tools, maintain state, self-correct, and integrate with external systems. Implement monitoring, evaluation, guardrails, error handling, and human-in-the-loop checkpoints for safe, long-running multi-step agent executions.

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.

Architect and productionize ML and GenAI solutions on Databricks, including RAG and agent systems, MLOps pipelines, model training/serving/monitoring, and advising customers and product teams on AI adoption.

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

Lead and grow a team building and scaling BEES's ML platform. Own roadmap and delivery across MLOps, pipelines, registries, feature stores, training and inference infrastructure, monitoring, governance, reliability, developer experience, standards, and stakeholder alignment to enable production ML at scale.