Top Machine Learning Jobs in Brazil

Leads J.P. Morgan’s Brazil Payments franchise, including Treasury Services sales, in-country strategy, client growth, product innovation, partnerships, operations, technology, risk management, regulatory representation, and talent development. Drives new business, market share, client wallet expansion, payments capabilities, and innovation roadmaps across liquidity, trade, merchant services, acquiring, acceptance, payment processing, and digital payments.

Support Mastercard Identity sales in Brazil by serving as the technical product expert for identity verification, fraud detection, and risk solutions. Lead discovery, solution design, proof-of-value testing, technical presentations, customer training, documentation, and onboarding. Explain machine learning, data science, APIs, and probability-based decisioning to technical and nontechnical stakeholders. Build customer relationships, attend conferences, provide market insights, and relay customer feedback to Product. Travel approximately 10%.

Design and build production AI applications, including advanced RAG pipelines, multi-agent workflows, and evaluation frameworks. Optimize system latency, throughput, scalability, resilience, and cost. Apply data science, machine learning, model monitoring, governance, and privacy practices. Provide technical leadership, mentor engineers, and collaborate with platform, data, AI, product, and consulting teams on robust AI-powered tools and integrations.

Leads and develops Applied Data Scientists across Brazil and India, delivering scalable data science, advanced analytics, and AI solutions for retail and CPG clients. Advises stakeholders, shapes commercial opportunities, manages end-to-end initiatives using agile methods, and promotes reusable science assets. Requires expertise in statistics, machine learning, customer and retail analytics, stakeholder management, team leadership, and Python, SQL, Spark, and Hadoop, plus fluent English and Portuguese.

Builds and maintains scalable batch and streaming data pipelines across on-premises and cloud environments. Designs data models, data flows, APIs, integrations, and access methods for reporting, dashboards, operational use, and data science. Translates business requirements into technical solutions, manages code integration, applies data governance, cleanses data, and supports complex project planning and delivery. Works independently across multiple dependencies and provides coaching to junior associates.

Develop, prototype, deploy, and validate AI, machine learning, and deep learning solutions for smart appliances, digital products, and cloud infrastructure. Build AI modules and product concepts, integrate models with existing architectures, and evaluate technologies including computer vision, NLP, large language models, RAG, and agentic workflows. Collaborate with global teams, research institutions, and cross-functional experts on consumer-focused innovation.

Analyze large-scale player data using statistics, machine learning, experimentation, and AI tools to improve game products. The role partners with Product Managers and Engineers on player retention, monetization, matchmaking, game economies, content customization, and product strategy. Responsibilities include designing experiments, building analytical tools and data products, automating workflows, solving open-ended business problems, and communicating actionable insights clearly.

Develop data-intensive applications and machine learning models for mobile game marketing. Responsibilities include modeling player behavior, measuring campaign impact and user lifetime value, optimizing acquisition campaigns, designing experiments, creating dashboards and data products, and building agentic AI workflows to monitor and improve marketing operations.

Leads the architecture and implementation of complex AWS cloud data solutions. Defines client data strategy roadmaps, supports pre-sales engagements as a data engineering subject matter expert, mentors technical teams, interviews candidates, and establishes data standards and operating procedures. The role requires extensive experience across traditional and modern data platforms, including data modeling, databases, BI, governance, big data, machine learning, generative AI, DataOps, infrastructure automation, and CI/CD.

Lead Electrolux Latin America's Data & Analytics organization and execute its regional data strategy. Manage multidisciplinary teams across governance, architecture, engineering, BI, and analytics; establish roadmaps, priorities, investment plans, and delivery governance. Oversee data platforms, pipelines, analytics environments, quality, security, compliance, and operational excellence. Partner with business leaders to improve customer experience, revenue, efficiency, and decision-making while advancing data literacy, AI, machine learning, and intelligent automation capabilities.

Lead and expand a strategic government or financial-institution client account. Build C-suite relationships, develop joint business plans, structure and negotiate complex multi-million-dollar SaaS deals, advocate for client needs, collaborate on tailored enterprise solutions, and achieve sales and profitability targets. The role requires deep financial-services knowledge, consultative enterprise selling expertise, strategic leadership, and travel up to 50%.

Leads complex digital strategy, product, platform, marketing, and AI-enabled projects from initiation through closure. Manages scope, budgets, roadmaps, resources, risks, delivery methodologies, and client communications. Oversees human review and guardrails for agentic workflows, facilitates stakeholder workshops, and leads cross-functional teams across strategy, design, engineering, QA, and data. Mentors project management staff, improves delivery processes, and ensures measurable business value and client satisfaction.

Lead the technical direction of an AI agent product, designing conversational AI, RAG pipelines, agent architectures, LLM evaluation, prompt management, monitoring, and observability. Develop proprietary machine learning models, productionize them with feedback loops, identify new AI use cases, and provide technical guidance across product teams. This hands-on role involves writing code regularly and partnering closely with Product in a remote Brazil-based environment.

Build and ship AI product features for Alti, including conversational AI, agents, automated routines, RAG pipelines, prompt strategies, and LLM evaluation systems. Establish monitoring and observability for AI features, help deploy ML models to production, and create continuous feedback loops. Collaborate with Product and Design to solve customer problems using AI and strengthen the team’s ML delivery practices.

Coordinate Brazil’s anti-money laundering and counter-terrorist financing program. Define quality assurance standards, review AML controls, assess financial crime data quality, identify root causes, track remediation, manage regulatory communications with Brazil’s Central Bank, and support market expansion through risk, control, reporting, and escalation processes.

Conduct research on frontier AI systems, including synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarking, and evaluation. Design rigorous experiments, datasets, prototypes, tooling, and research workflows; train and assess models; analyze results; and translate findings into scalable AI products. Collaborate across research, engineering, product, and operations teams, communicate technical conclusions, contribute to publications or open-source work, and mentor engineers and researchers.

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.

Drive new enterprise business and strategic account growth for FICO’s analytics and decisioning solutions in Brazil. Build executive relationships, create pipeline, structure and close complex multi-million-dollar SaaS deals, develop joint business plans, advocate for clients, and collaborate with internal teams. The role focuses on banking and financial services customers, including credit risk, fraud prevention, lending, and account management, with travel of up to 50%.

Drive adoption, engagement, renewal, and expansion for a large portfolio of cybersecurity customers through one-to-one and scaled communications. Lead onboarding, webinars, digital customer journeys, health monitoring, and escalation resolution. Collaborate with Renewals, Sales, Product, and Customer Success teams to identify customer risks and scale successful engagement programs. Manage high task volumes while improving customer outcomes and retention.

Supports application engineering projects involving Asset Performance Management tools and Machine Learning. Responsibilities include creating technical documents and reports, analyzing rotating and static industrial equipment, configuring software, and collaborating with teams to meet deadlines and quality standards.

Leads data engineering, Palantir Skywise architecture, and AI solution development for Airbus manufacturing and operational environments. Builds scalable pipelines, analytical workflows, machine learning and generative AI applications, and enterprise data foundations. Oversees Alteryx and Tableau platforms, establishes governance, mentors technical teams, translates business challenges into data products, and supports AI Center of Excellence initiatives. The role is onsite 60% across several U.S. locations and requires approximately 10% travel.

Own fraud performance across cards, ACH, and digital wallets by analyzing fraud vectors, payment mechanics, and emerging threats. Design product-based controls, authentication steps, holds, and friction strategies; partner with Product, Engineering, and Data Science; run experiments to measure fraud reduction and conversion impact; and maintain decisioning logic in Sardine or Oscilar. The role requires advanced SQL and Python, payment rail expertise, analytics, machine learning knowledge, and strong cross-functional communication.

Own fraud performance across cards, ACH, and digital wallets by analyzing fraud vectors, designing product-based controls, optimizing authentication and payment friction, and partnering with Product, Engineering, and Data Science. Conduct payment-rail threat analysis, build and validate experiments, inform fraud-model features, and manage decisioning logic in Sardine or Oscilar. The role requires deep expertise in payment mechanics, advanced SQL and Python analytics, experimentation, and fraud-risk strategy.

Build and operate a governed people-data platform supporting workforce analytics and AI use cases. Design scalable data models, production pipelines, integrations, quality controls, lineage, privacy controls, and reliability practices. Own the platform’s AI-readiness and infrastructure roadmap, monitor performance, manage incidents, and partner with People Analytics, HR Technology, Security, Legal, and Enterprise Data teams. Translate approved requirements into secure, production-ready technical solutions using Workday and Azure-based data technologies.

Lead applied AI engineering across generative and discriminative use cases, including scalable content generation, gamification, benchmarking, analytics, and multimodal behavior classification. Own AI-first SDLC practices, MCP and ML tooling, prompting standards, application benchmarks, roadmap development, and end-to-end deployment and maintenance of AI systems. Establish engineering standards for quality, scalability, and AI-first development while collaborating closely with product and engineering leadership.