Top Machine Learning Jobs in Brazil

Lead global smart manufacturing and automation strategy for Wound Closure & Healing. Drive controls, MES, IIoT, AI/vision, robotics, and Industry 4.0 initiatives; manage roadmaps, harmonize platforms across sites, serve as MES BPM, mentor teams, support business cases, and ensure quality, compliance, EH&S, and financial reporting. Travel ~20%.

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 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.

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.

Supports business development and client proposals by researching healthcare business problems and developing innovative analytics solutions. Assists with predictive modeling, patient journey analysis, HCP targeting, and alerts using statistical and machine learning methods. Translates client needs into methodologies and communicates clinically and commercially meaningful findings. Manages assigned tasks and timelines, supports automation and standardization, and contributes to new offerings and team initiatives.

Leads digital innovation initiatives across customer, employee, factory, and product experience domains. Identifies opportunities, facilitates ideation workshops, prioritizes concepts, develops digital strategies, and executes proof-of-concepts using agile and Design Thinking methods. Collaborates with business, IT, vendors, and matrixed teams to create measurable value, influence stakeholders, evangelize emerging technologies, and advance enterprise digital transformation.

Leads Johnson & Johnson’s enterprise HR AI and automation strategy across the Hire-to-Retire lifecycle. Oversees teams delivering generative AI, conversational AI, machine learning, RPA, and workflow solutions; establishes product roadmaps, governance, adoption strategies, KPIs, and value realization measures. Partners with HR, IT, product, and business leaders to improve employee experiences, simplify processes, reduce manual effort, and drive global digital transformation. The role also requires executive influence, responsible AI oversight, and leadership of innovation-focused teams.

Leads Johnson & Johnson’s enterprise HR AI and automation strategy across the Hire-to-Retire lifecycle. The role manages teams delivering generative AI, conversational AI, machine learning, workflow orchestration, and RPA capabilities; partners with HR, IT, product, and business leaders; establishes roadmaps and governance; drives adoption and transformation; and measures business value, employee impact, and operational outcomes.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Annotate, evaluate, and curate text, video, and geographic data to train and improve AI and machine learning models. Follow detailed guidelines, conduct basic research, maintain annotation quality, identify data patterns, provide process feedback, meet deadlines, and adapt to evolving instructions. The role is full-time and remote in Brazil, with one required visit to the São Paulo office to collect equipment.

Leads enterprise sales strategy and revenue growth for Epiq’s AI-powered eDiscovery, legal technology, compliance, analytics, and information governance solutions. Develops pipelines, manages complex consultative sales cycles, expands strategic accounts, and engages executive stakeholders across corporations, law firms, government, and regulated industries. Acts as an AI and legal technology subject matter expert, supports responsible AI adoption, partners cross-functionally on solution development and delivery, and represents Epiq through market development, thought leadership, and strategic partnerships.

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.

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.

Lead detection and analytics research across cloud, identity, endpoint, network, and application environments. Embed security expertise into product and R&D, apply AI/LLM and ML techniques for scalable detections, analyze attacker techniques, measure detection quality, and contribute research outputs and tooling.

Lead a security governance and risk management team to define frameworks, drive compliance (ISO/PCI), manage audits and remediation, report KPIs to leadership, embed security into products and vendors, and run awareness and AI-driven automation initiatives.

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.

Lead full-cycle technical recruiting for Data/ML, Platform, and Engineering; build predictable pipelines, design structured interview processes and scorecards, run high-signal screening, partner with senior leadership, and improve recruiting workflows to hire and retain high-performing talent.

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.

Partner with LATAM sales to lead technical discovery, deliver demos and POCs, design solution architectures, resolve technical blockers, and support integrations across Telnyx products (voice, messaging, wireless, networking, storage, and AI). Act as technical expert through the sales cycle and convey technical value to both technical and executive audiences.

Create executive-ready dashboards and visualizations, leverage AI/ML and automation to build data products, manage commercial master data, synthesize large datasets into scalable models, collaborate with local analytics and engineering teams, communicate commercial results to senior leadership, own and govern Commercial Performance data assets, and deliver ad-hoc analyses on pricing, market share, and volume performance.

Design, build, and optimize a multi-region, highly-available Java/Scala microservices data pipeline processing thousands of messages/sec. Improve performance, implement fraud-detection pipelines with ML (Kafka/Kafka Streams), deploy to multi-cloud Kubernetes, and push frequent production releases to maintain five-nines uptime.

Annotate and manage training/test datasets, run model training, evaluate model performance, perform manual QA and error analysis, and refine annotation guidelines for NLP/ML projects.

Hands-on credit data scientist responsible for building and monitoring predictive credit and churn models, creating feature books from transactional data, implementing AI-driven credit automation, backtesting portfolio strategies, building propensity-to-pay models for collections, and designing real-time KPI dashboards to track credit and recovery performance.