Top Machine Learning Jobs in Rio de Janeiro

Build scalable Python backend APIs, ML platforms, MLOps pipelines, and production LLM systems. Develop RAG and Generative AI workflows, model-serving infrastructure, feature pipelines, observability, prompt management, and multi-tenant architectures. Integrate Azure OpenAI, vector databases, OCR services, and enterprise systems while optimizing performance, reliability, security, and cost. Write maintainable, testable code; troubleshoot distributed applications; participate in design reviews and agile ceremonies; and collaborate with client-facing teams on technical requirements.

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.

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%.

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.

Designs and deploys production-grade AI agents, LLM applications, RAG systems, multi-agent workflows, and scalable AI pipelines. Builds Python SDKs, integrates enterprise platforms and identity providers, implements MLOps and LLMOps practices, and establishes safety, governance, evaluation, observability, and human-in-the-loop controls. Collaborates with engineering, data, and product teams to deliver secure, domain-specific AI solutions.

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.

Architect, develop, and deploy machine learning systems for chatbot and search applications. Design experiments, analyze structured and unstructured data, improve models, and develop LLM-powered product features using prompt experimentation, agent evaluation, and AI guardrails. Provide technical leadership to data scientists and contribute to Data Science chapter decisions, reviews, and knowledge sharing.

Architect, develop, and deploy machine learning systems for chatbots, search, and other product features. Design experiments, analyze structured and unstructured data, improve models, and develop LLM-powered applications using prompt evaluation, agents, guardrails, and proofs of concept. Provide technical leadership within the Data Science chapter and contribute to technical decisions, reviews, and knowledge sharing.

Architects, develops, and deploys machine learning systems for chatbots and search. Designs experiments, analyzes structured and unstructured data, improves models, and applies scientific methods to LLM-powered applications. The role evaluates prompts, agents, capabilities, and guardrails while building generative AI proofs of concept. It also provides technical leadership and contributes to Data Science chapter decisions, reviews, and knowledge sharing.

Architects, develops, and deploys machine learning systems for chatbot and search applications. Designs experiments, analyzes structured and unstructured data, and develops LLM-powered applications using prompt experimentation, agent evaluation, guardrails, and generative AI proof-of-concepts. Provides technical leadership within the Data Science chapter and collaborates with product, design, engineering, and machine learning teams.

Leads Snowflake’s LATAM Solutions Engineering team in Brazil, managing sales engineers while supporting technical sales cycles, demonstrations, proofs of concept, customer presentations, and regional technical-win forecasting. Partners with sales, channel partners, product, engineering, marketing, and services teams to achieve quota goals, identify customer solutions, improve win rates, and expand into new territories. Responsibilities also include recruiting, interviewing, coaching, developing team talent, and advising revenue leadership on sales strategy and product needs.

Design, optimize, and deploy Retrieval-Augmented Generation systems and large language model applications for clients. Responsibilities include fine-tuning models, improving retrieval and generation performance, building GenAI product frameworks such as search, chatbots, and summarization tools, establishing ML infrastructure, writing scalable production code, and providing technical leadership on AI/ML opportunities.

Join Viridien’s Subsurface Imaging team to apply physics, mathematics, and geophysics to seismic imaging challenges. Develop, test, and implement imaging techniques using large-scale datasets and high-performance computing. Collaborate with geophysicists, researchers, scientists, and software engineers to improve algorithms, tools, and workflows. Analyze results, communicate findings, and potentially contribute to publications and presentations while receiving structured training and mentorship.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Owns financial data and BI product strategy across Quote-to-Cash and Order-to-Cash processes. The role identifies operational gaps, translates finance and revenue lifecycle needs into PRDs and roadmaps, validates pricing and contract data, and develops dashboards and AI/ML analytics opportunities. It partners with Sales, Legal, Accounting, Finance, Product, and data engineering teams to improve downstream reporting and decision-making.

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.

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.

Design, deploy, and optimize large-scale recommender systems and machine learning pipelines. Build recommendation models using architectures such as Wide & Deep, Two-Tower, Transformer, embedding-based, autoencoder, and sequential models. Process data with Databricks and Spark, integrate models into production, monitor performance, conduct experimentation and A/B testing, and collaborate with engineering, data science, and business 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.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.