Top Machine Learning Jobs in Brazil

Lead the design, development, deployment, and continuous improvement of scalable production AI solutions. Build LLM, RAG, agentic AI, machine learning, and document intelligence systems using Python, Azure, DevOps, IaC, Docker, Kubernetes, and MLOps. Own architecture, testing, evaluation, monitoring, security, governance, and operational support while translating business needs into measurable outcomes. Provide technical leadership, mentorship, stakeholder collaboration, and influence enterprise AI engineering standards and platforms.

Serve as a technical advisor within Expert Services to design and deliver bespoke integrations, data strategies, and custom implementations of the Braze platform. Drive complex technical projects, support onboarding and SDK/API integrations, troubleshoot strategic technical issues, document architectures, and collaborate with Sales, Product, Engineering, and Customer Success to maximize customer adoption and time-to-value.

Build and deploy statistical and ML models (especially demand forecasting) to improve sales forecast accuracy. Analyze data, create actionable insights, collaborate with stakeholders and regional teams, set analytics standards, monitor model performance, and deliver dashboards and visualizations for supply chain decision-making.

Own BI product strategy for financial systems supporting Quote-to-Cash and Order-to-Cash processes. Identify operational friction and translate it into BI, AI, and machine learning opportunities. Create PRDs, roadmaps, and functional requirements while partnering with finance, legal, sales, product, delivery, and engineering teams. Ensure quoting, deal structuring, billing, contract, entitlement, and revenue-recognition data is accurately represented in downstream data products and dashboards.

Lead the full product lifecycle by owning roadmaps, translating business priorities into executable plans, defining features with engineering and UX/UI teams, and driving timely delivery. Conduct user research, establish product metrics, lead client demos, support go-to-market positioning, and align product development with broader innovation goals. Manage cross-functional teams, including ML engineers, while iterating products based on user feedback.

Annotate, evaluate, and curate Portuguese text, video, and geographic data to train and improve generative AI and machine learning models. Follow detailed guidelines, conduct basic research, maintain annotation quality, identify data patterns, provide process feedback, meet deadlines, and complete required training, client testing, and interviews. This is a full-time remote role in Brazil, with a one-time São Paulo office visit to collect equipment.

Owns BI product strategy for Quote-to-Cash and Order-to-Cash financial systems. Identifies operational pain points and translates them into BI, AI, and machine learning opportunities. Creates product requirements, roadmaps, and functional specifications while partnering with finance, legal, product, technical delivery, and engineering teams. Ensures quoting, deal structuring, billing, contract, and revenue recognition processes are accurately represented in downstream data products and dashboards.

Two-year rotational graduate program spanning engineering, IT, freight services, and digital intelligence. Participants contribute to projects involving locomotive systems, propulsion, controls, automation, software, data analytics, AI, cloud technologies, reliability, testing, and continuous improvement before transitioning into a permanent role. The program requires an engineering bachelor's degree, recent or upcoming graduation, strong English proficiency, travel availability, and prior academic or extracurricular experience.

Partner with IT and Global Business Service Analytics & Insights teams to provide architecture guidance, create solution documentation and diagrams, support deployments and governance, monitor vulnerabilities and support tickets, and coordinate stakeholders to ensure SLA adherence and project delivery.

The Senior Data Developer extends and maintains existing code repositories, builds ETL/ELT pipelines, integrates enterprise data from BigQuery and SAP, and designs database structures. Depending on expertise, the role also supports front-end and backend application development, scheduled jobs, and machine learning for computer vision and forecasting. The developer follows Git best practices, communicates clearly, and collaborates with distributed cross-functional teams across supply chain, manufacturing, logistics, and procurement initiatives.

Advise clients on antitrust eDiscovery compliance using machine learning and generative AI. Build and validate TAR/AI models (Epiq AI, Relativity, Reveal, Brainspace), craft LLM prompts, draft defensible protocols, train/transfer workflows to review teams, and support client-facing, pre-sales, and thought-leadership activities. Must manage multiple projects and meet deadline-driven schedules.

Design, build, and maintain scalable data pipelines and workflows on GCP. Contribute across the project value chain, including infrastructure, data collection, machine learning models, REST APIs, front-end and back-end development, testing, and continuous deployment. Collaborate with diverse teams, communicate technical concepts to business stakeholders, troubleshoot complex issues, prioritize work, meet deadlines, and mentor team members.

Owns end-to-end LATAM marketing across Brazil and Mexico, including brand, demand generation, ABM, partner marketing, events, localization, customer case studies, and pipeline reporting. Partners with sales, account teams, HQ marketing, resellers, systems integrators, and platform partners to build regional programs and market presence. Translates complex AI and developer products into compelling messaging for enterprise buyers and technical audiences.

Leads fraud-domain pre-sales across Latin America, the Caribbean, and Brazil. Partners with clients to discover challenges, develop proposals, business cases, ROI studies, demonstrations, and executive presentations. Supports workshops, proof-of-concept engagements, negotiations, account planning, go-to-market strategy, and thought leadership. Applies expertise across transactional, identity, application, monitoring, KYC, internal, and first-party fraud while collaborating with sales and platform teams. Travel is required up to 50%.

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.

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.

Conduct exploratory analysis, statistical modeling, experimentation, forecasting, and machine learning for marketplace and pricing systems. Analyze supply, demand, elasticity, conversion, and pricing behavior; build predictive models; improve data quality and analytical foundations; contribute to production ML; and communicate actionable recommendations to Product, Engineering, Pricing, and business stakeholders.

Leads consultative discovery, technical qualification, solution design, executive engagement, sales campaigns, and customer presentations for AspenTech solutions across Metals & Mining, LNG, Specialty Chemicals, and Polymer industries in LATAM. Translates industry challenges into measurable business value, develops industry-specific messaging, supports sales teams, informs product management, and trains account managers and solution consultants. Requires extensive industry software-selling experience and travel up to 35%.

Support deployment and maintenance of fraud-detection solutions: assist with ETL configuration, detection implementation, feature rollout, pipeline optimization, and cross-team client engagement under senior data scientists.

Join Artefact LatAm's Data & Consulting team to design and implement end-to-end analytics and ML solutions. Work across data collection, processing, EDA, model development and production, translate technical findings for business stakeholders, collaborate with consultants and engineers, and optimize models for performance and scalability under senior guidance.

The role involves building relationships with senior clients, presenting FICO's analytics platform, and managing sales targets within financial services.

Design, build and own end-to-end data solutions and infrastructure. Implement scalable pipelines using cloud and big-data technologies, optimize performance, create REST APIs and CI/CD, coach teammates, and communicate technical solutions to business stakeholders.

Supports the Solutions Engineering team by creating SQL demonstrations, exploratory analyses, queries, reports, visualizations, prototypes, and proof-of-concepts using public and customer datasets. Assists with environment setup, task automation, cloud infrastructure, and technical community initiatives such as events, webinars, training, and content creation. Collaborates with technical leadership while gaining practical experience in data science and analytics.

As a Data Scientist at Zicasso, you will analyze complex datasets, develop predictive models, and optimize customer experiences using AI and machine learning techniques, while collaborating with cross-functional teams.

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.