Top Machine Learning Jobs in Fortaleza

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.

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.

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.

The Data Scientist will lead data-driven decision-making, develop machine learning models, design automated pipelines, and improve product performance.

The Senior Machine Learning Engineer will build and optimize ML systems for CRM marketing, collaborating with cross-functional teams to impact customer engagement and product functionality.

Design, build, and deliver enterprise-grade Generative AI/ML platform services, reusable frameworks, APIs, and agentic applications. Implement scalable model deployment, inference, monitoring, CI/CD, event-driven streaming (Kafka), and secure microservices while collaborating with architects, data scientists, and stakeholders to ensure governance, scalability, and operational excellence.

The AI/ML Engineering Manager will lead a team of ML engineers, manage client engagements, shape architecture, and drive pre-sales while ensuring team growth and performance.

Own product direction for ML platform capabilities across the end-to-end ML lifecycle. Set vision and roadmap, define standards and tooling, drive adoption with data science and engineering teams, deliver templates/CLIs/workflows, and improve model deployment, observability, and operational practices to enable scalable, reliable ML solutions.

Design, build, and deploy agentic LLM workflows that plan, call tools, maintain state, self-correct, and integrate with external systems. Implement monitoring, evaluation, guardrails, error handling, and human-in-the-loop checkpoints for safe, long-running multi-step agent executions.

Seeking a Software Engineer with 5+ years in AI/ML to design and implement scalable web APIs and applications, focusing on generative AI solutions, while engaging cross-functional teams and mentoring junior developers.

Develop and implement LLM workflows, collaborate with teams on AI/ML solutions, ensure quality delivery using CI/CD practices, and support technical duties.

As a Machine Learning Solutions Architect, you will design and implement data solutions, provide thought leadership, and ensure scalable deployment of machine learning models.

Design, develop, and deploy machine learning pipelines. Implement MLOps practices and optimize models. Collaborate on data pipelines and cloud deployment.

Design, build, evaluate, and deploy production-grade LLM and classical ML solutions. Create retrieval and agentic workflows, integrate AI into client apps, implement evaluation frameworks, optimize prompts and pipelines, and collaborate with product teams through discovery to production support.

Build, deploy, and maintain production-grade ML models and data pipelines in cloud environments. Perform EDA and feature engineering, monitor model performance and drift, and collaborate with engineering and business stakeholders. Contribute to AI/LLM initiatives and ensure solutions operate reliably in production.