Top Machine Learning Jobs in Rio de Janeiro

This role involves building and optimizing LLMs and AI systems for public safety, focusing on real-time application and collaboration with various teams.

The Senior Tech Product Manager will lead the development of AI-driven, data-focused products, ensuring client engagement and product success through strategic planning and stakeholder collaboration.

The Lead Product Manager will oversee the lifecycle of data and AI products, cultivate stakeholder relationships, drive product strategy, run experiments, and ensure successful market delivery.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

Identify Brazilian species through images and audio, support biodiversity surveys, and train machine learning models by annotating data.

As an Applied AI Researcher, you will develop algorithms for diverse data modalities, collaborate on innovations, and lead research dissemination in GenAI.

As Lead Product Manager, you will drive the development of data and AI products, manage stakeholder relationships, and guide product strategy in dynamic pricing.

The Senior Data & AI Product Manager will drive product strategy and development for data-driven products, utilizing AI and machine learning to enhance customer experience and business outcomes, while promoting collaboration among stakeholders.

The Senior Machine Learning Engineer will enhance Xometry's ML capabilities, develop models for cost prediction, lead technology evaluations, and collaborate on AI solutions.

Lead the design and implementation of AI solutions, integrating ML models into applications, driving strategy, and mentoring teams in AI best practices.

Lead the search experience and infrastructure at Superbet, focusing on personalization and experimentation to enhance user engagement and discovery across platforms.

As an Analytics Engineer, you'll refine data, build models, enable self-service analytics, and collaborate with various teams to improve customer insights.

The Lead Data Scientist drives analytics initiatives, develops statistical models, mentors junior team members, and communicates insights to stakeholders.

Lead a team of ML engineers to build personalization systems, architect multi-stage ranking systems, and mentor engineers while driving model quality improvements.

The contractor will develop machine learning algorithms, maintain data pipelines, conduct data analysis, and validate models through experimentation.

The Principal Machine Learning Engineer will define personalization strategies, solve complex ML challenges, and lead innovative projects influencing business outcomes.

The role involves establishing the technical vision for personalization strategies, solving complex ML challenges, and mentoring senior engineers.

Lead the technical vision for personalization at Launch Potato, architecting ML solutions and mentoring senior engineers while driving strategic alignment across teams.

Lead the technical vision and implementation of advanced ML systems focused on personalization, guiding teams through complex challenges and innovative solutions.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

The Senior Project Manager will lead Martech teams, manage project timelines and budgets, ensure client satisfaction, and drive Agile methodologies.

You will design and implement AI systems to assess and improve the quality of web datasets, collaborating with data, product, and engineering teams.

Lead the Core & MLOps team to build and maintain the foundational infrastructure for scalable data services, with responsibilities in technical leadership, MLOps excellence, and team management.

Lead engineering teams in automation and corporate systems, promoting technical excellence and aligning with business objectives. Drive AI adoption for operational efficiency and manage engineering processes.

Lead the development of device intelligence and fingerprinting systems, integrating machine learning capabilities, and enhancing device recognition through advanced algorithms and data analysis.