Top Machine Learning Jobs in Brasilia

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.

Design, build, validate, and productionise predictive and decisioning models (fraud, risk, onboarding, pricing, CLV). Frame business problems, run experiments and causal analyses, engineer data pipelines, monitor model performance and drift, and integrate models into product workflows while contributing to team tooling and standards.

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.

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.

Design, architect, and govern scalable data platforms (data lake/warehouse). Engage stakeholders to gather requirements, implement ETL pipelines, optimize performance, and manage data ingestion using Hadoop/Spark/Kafka/Airflow and AWS tools. Support data modeling, security, and workflow orchestration.

Join an agile team building HealthTech applications: design and implement scalable microservices, integrate ML and third-party systems, conduct code reviews, author technical documentation, debug and optimize systems, and own services over time while maintaining high code quality and delivery standards.

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.

The Refining and Petrochemical Process Optimization Engineer will optimize manufacturing processes using AI, working with plant personnel and leading project implementations.

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.

Support the full data workflow: ingest and structure data, perform cleaning and validation, run exploratory analysis and visualizations, assist with ML/DL experiments and model evaluation, and contribute to predictive maintenance and ERCOT market analytics projects.

The Fraud Strategy Specialist will develop and manage fraud prevention strategies, enhance analytics, collaborate with teams, and ensure a seamless customer experience.

The Fraud Strategy Specialist will design fraud prevention strategies, develop anomaly detection systems, and collaborate with multiple teams to enhance safety while enabling customer growth.

The Senior Machine Learning Engineer will enhance Xometry's ML capabilities, develop models for cost prediction, lead technology evaluations, and collaborate on AI solutions.

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.

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.

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.

Design, build, and maintain scalable data pipelines, vector stores, feature stores, and LLM-driven workflows. Implement RAG, prompt engineering, model fine-tuning, and managed LLM deployments on cloud. Optimize big-data processing, enable real-time inference, build analytics/NL query dashboards, document processes, and partner with stakeholders to translate requirements into production BI/ML solutions.

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

Lead end-to-end supply chain transformation engagements for commercial and utility clients. Advise executives, design future-state supply chain architectures, oversee implementation across planning, procurement, logistics, and analytics, build financial value cases, and manage multidisciplinary teams to deliver measurable operational and financial results.

Lead end-to-end supply chain transformation engagements, advising executives and directing multidisciplinary teams to improve planning, procurement, logistics, inventory, and supplier performance. Design future-state architectures, build business cases, drive implementation, grow client relationships, and scale practice capabilities while delivering measurable operational and financial impact.

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

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.