Top Machine Learning Jobs in Brazil

The role involves consulting with clients to understand their business needs, designing solutions, creating demonstrations, and preparing sales proposals. It requires strong communication and problem-solving skills, along with the ability to analyze business benefits and develop sales strategies.

As an AI Operations & Automation Specialist, you will optimize finance and HR operations through automation, AI implementation, and process improvement while ensuring data integrity and supporting various teams in the company.

The Business Development Manager drives growth by managing key accounts, identifying new business opportunities, and collaborating with marketing and sales to maximize profitability.

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

The Data Product Manager will lead AI-powered computer vision initiatives, collaborating with global teams, managing product planning, and ensuring successful delivery and adoption across markets.

The AI Deployment Lead will engage with clients, identify operational challenges, prioritize solutions, and drive the adoption of the Avra platform while collaborating with technical teams and providing feedback for product improvement.

This role involves leading industrial automation projects in the pulp and paper sector, focusing on MES solutions and technical delivery, while mentoring engineers and ensuring compliance with safety and cybersecurity standards.

The Senior Data Scientist will design and build scalable data products, develop machine learning models, and collaborate with various teams to drive impactful data solutions.

The Product Owner will manage the product backlog, translate business needs into user stories, ensure product alignment within Agile teams, and drive continuous improvement of product outcomes, especially in AI/data-driven products.

The Machine Learning Engineer will develop distributed ML systems, collaborate on model deployment, optimize feature extraction, and enhance ML capabilities.

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 Python Engineer will design and develop AI/ML-driven applications, optimize models, and collaborate with teams to deliver scalable solutions.

The Machine Learning Architect will design scalable AI and ML solutions, lead architecture development, implement MLOps, and collaborate with teams for effective machine learning capabilities.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

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.

Responsible for developing and deploying machine learning models to optimize payment transaction processing and reduce false declines, while ensuring real-time performance and monitoring.

Drive machine learning initiatives by collaborating with teams to produce AI solutions, develop models, and communicate with stakeholders. Responsible for building scalable cloud-native applications and pipelines.

Join Blue Orange Digital as a Machine Learning Engineer, focusing on product development, client support, and testing within AI products, especially in financial services. Responsibilities include modeling, data pipeline writing, training ML models, and ensuring quality control.

This role involves designing and implementing scalable ML and AI solutions, mentoring team members, and driving technical strategy in cloud environments.

The Associate Machine Learning Engineer will assist in designing and producing ML solutions, support application integrations, work on cloud offerings, and prepare technical documentation while staying updated on AI advancements.

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.