Top Machine Learning Jobs in Rio de Janeiro

Design and scale agentic multi-agent systems that connect LLMs to internal APIs and tooling. Build production Python microservices, implement RAG, fine-tuning, and prompt engineering, and develop evaluation pipelines for LLM agents. Integrate vector databases and MCP, collaborate with product and conversation design, and ensure responsible, compliant AI-powered customer support experiences at scale.

Design, optimize, and deploy Retrieval-Augmented Generation systems and large language model applications for clients. Responsibilities include fine-tuning models, improving retrieval and generation performance, building GenAI product frameworks such as search, chatbots, and summarization tools, establishing ML infrastructure, writing scalable production code, and providing technical leadership on AI/ML opportunities.

As a Principal Technical Recruiter, you'll lead high-level searches while integrating AI into recruiting workflows, manage client relationships, and coach on using the AI recruiting platform, Moon Engine.

Build and maintain internal web applications and tools (dashboards, search, annotation, account management) with scalable, secure front-end code. Lead projects, reduce technical debt, collaborate across time zones, and deliver well-tested, extensible solutions that explain ML outputs and improve authentication workflows.

Work with client data to develop fraud-detection models: clean and preprocess data, engineer features, build and tune ML models, create scalable pipelines, collaborate with clients and internal teams, communicate results, and contribute technical leadership and product enhancements.

Provide L2 application support: troubleshoot and resolve production issues, analyze logs and root causes, manage incidents and change processes, automate monitoring/health restoration, build runbooks, and produce health and trend reports to improve application stability.

Create and review realistic, locale-specific robotics and natural sciences tasks in Brazilian Portuguese; apply scoring rubrics; evaluate and score AI and human responses for accuracy and regulatory alignment; produce gold-standard solutions and expert feedback.

As the Head of Credit for Brazil, you will develop credit policies, lead analytics teams, build risk models, and collaborate across teams to drive growth and ensure quality in credit offerings.

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.