Top Machine Learning Jobs in Sao Paulo

Lead strategy and lifecycle for AI- and data-driven products, defining vision, roadmaps, and AI-powered features (LLMs, RAG, agentic architectures). Drive product discovery, validate hypotheses, manage complex integrations (CRM, dialers), ensure responsible AI practices and compliance, partner with engineering and data teams, prioritize backlog, assess financial/operational AI costs, and communicate value to executives and stakeholders.

Design and deploy a multi-agent orchestration layer for conversational AI, build production-grade Python ML services, lead end-to-end ML projects, establish team best practices, mentor engineers, and ensure secure, scalable, high-performance customer-facing AI systems.

Analyze large federal and state economic datasets, automate data collection and scraping, and rapidly publish clear, data-driven reporting on market-moving indicators. Collaborate with reporters and visual journalists, file public-records requests, and use emerging technologies including AI to enhance real-time coverage.

As a Data Engineer, design and maintain data pipelines and infrastructure, collaborate with teams for efficient data delivery, and optimize data storage and retrieval processes.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.

Own fraud performance across cards, ACH, and tokenized wallets. Diagnose fraud vectors, design product-based controls, run experiments (A/B tests), partner with Data Science and Engineering, and maintain orchestration rules to reduce fraud while minimizing friction for legitimate customers.

Own fraud performance across cards, ACH, and tokenized wallets by diagnosing payment-frail vectors, designing product-first controls, running A/B experiments, partnering with Product/Engineering and Data Science, and maintaining orchestration/rule logic to reduce fraud while minimizing friction.

Responsible for managing a team of cloud engineers, overseeing technical tasks, engaging with clients, mentoring team members, and ensuring technical accountability on projects.

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

Lead and define architecture, oversee scrum delivery, delegate tasks, supervise system changes, conduct security audits, liaise with stakeholders, write reports, and hire/train technical staff for scalable backend and data/AI solutions.

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.

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.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

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.

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.

Lead LATAM partner ecosystem strategy and execution across GSIs, OEMs, acquirers, payment processors, hyperscalers, and ISVs. Drive partner-sourced and partner-influenced revenue, joint GTM plans, partner recruitment/onboarding, enablement, and performance governance using BI and PRM tools. Collaborate with sales, marketing, product, and customer success to scale Feedzai's footprint in LATAM.

Lead end-to-end delivery of Google Cloud adoption engagements. Coordinate cross-functional teams and executive stakeholders, scope and plan projects, mitigate risks, track adoption and utilization, integrate change management, mentor teams, and drive successful enterprise cloud migrations and modernization.

Lead analytical projects to generate data-driven insights and implement AI-assisted solutions. Partner with clients and internal teams to map processes, identify high-impact opportunities, scope and manage analytics work, and track outcome realization. Use descriptive and predictive methods, ensure data integrity, develop reporting, evaluate customer interactions, and present recommendations to stakeholders, including executives.

Full-cycle enterprise sales role focused on acquiring and expanding accounts in Brazil. Evangelize Replit, run demos and hackathons, manage deals and CRM (HubSpot), collaborate with product/engineering, negotiate contracts, support customer adoption, and gather feedback. Travel up to 25%.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

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