Role Description A área de Ciência de Dados tem como objetivo explorar novas fronteiras para capacitar as empresas a responderem às suas questões mais urgentes. Pioneiros no processamento analítico intensivo de dados em larga escala e altamente paralelo, nossa missão é desenvolver uma abordagem totalmente inovadora para gerar significado e valor a partir de conjuntos de dados na escala de petabytes, criando novas metodologias, ferramentas, métodos estatísticos e modelos. Além disso, trabalhamos em colaboração com acadêmicos de destaque, especialistas do setor e engenheiros altamente qualificados para capacitar nossos clientes a gerar insights sofisticados e inovadores a partir de volumes massivos de dados. Como MLOps Engineer, você será responsável por: - Projetar, implementar e gerenciar pipelines robustos de MLOps para implantação, monitoramento e manutenção de modelos de machine learning em ambientes de produção. - Trabalhar em estreita colaboração com cientistas de dados, engenheiros de software e equipes de DevOps. - Acelerar a entrega de soluções avançadas de IA generativa. - Impulsionar a evolução das estratégias de deployment de machine learning da organização. Junte-se a nós como MLOps Engineer em nossa equipe de AI-Centric Engineering (Office of the CTO) no Brasil (remoto) para fazer o melhor trabalho da sua carreira e gerar um impacto social profundo. Company Description Dell Technologies é uma família única de negócios que ajuda indivíduos e organizações a transformar como trabalham, vivem e se divertem. Junte-se a nós para construir um futuro que funcione para todos, porque o progresso depende de todos nós. Dell Technologies é comprometida com o princípio da igualdade de oportunidades de emprego para todos os funcionários e com a provisão de um ambiente de trabalho livre de discriminação e assédio. Leia a política completa de Igualdade de Oportunidades de Emprego. Visite nossa página do Culture Code para saber mais sobre como trabalhamos e lideramos.

Role Description We are looking for a Machine Learning Engineer to join our team and help build next-generation AI-powered workplace assistants. In this role, you will work with modern Generative AI technologies, agentic frameworks, and machine learning models to create smart, collaborative solutions. The position is fully remote, offering flexibility and opportunities to work with global teams. We at Sigma Software value innovation, engineering excellence, and continuous learning. This is a great opportunity to work on cutting-edge AI initiatives, influence product direction, and grow together with experienced professionals in an open and supportive environment. - Develop and integrate ML, NLP, and Generative AI models - Build and optimize agentic workflows using LangChain, LangGraph, or similar frameworks - Develop LLM-powered solutions using modern Generative AI technologies - Prototype internal tools and interfaces with Streamlit or Gradio - Collaborate with engineering and product teams to deliver AI-driven features - Manage development and runtime environments with Docker - Maintain clean and scalable code using Git-based workflows - Query and analyze structured data using SQL - Contribute to model deployment and operations in a cloud environment (primarily Azure) Qualifications - 3+ years of commercial experience in software engineering or AI/ML development - Strong proficiency in Python - Hands-on experience with Generative AI applications and Large Language Models - Experience with agentic AI frameworks such as LangChain or LangGraph - Solid understanding of machine learning and NLP fundamentals - Experience with ML frameworks including PyTorch or TensorFlow - Familiarity with Streamlit, Gradio, or similar prototyping tools - Practical experience with Git, Docker, and cloud platforms - Good knowledge of SQL - Understanding of software engineering best practices and estimation processes - Upper-Intermediate level of English Requirements - Experience with additional agentic AI or LLM orchestration frameworks - Experience building Retrieval-Augmented Generation solutions - Experience with MLOps practices and model deployment - Confidence working in Linux terminal environments Benefits - Strong analytical and problem-solving skills - Ability to work independently and proactively - Excellent communication and collaboration skills - Passion for innovation and modern AI technologies - Focus on code quality and continuous improvement

• Design, develop, and optimize scalable Machine Learning models for advertising intelligence and forecasting systems • Analyze large-scale historical and real-time datasets to improve forecasting accuracy and monetization strategies • Build and maintain distributed data processing pipelines using Spark and related Big Data technologies • Develop production-ready ML solutions using Python within AWS cloud infrastructure • Research, evaluate, and implement Machine Learning algorithms suitable for high-load AdTech environments • Improve model performance, scalability, reliability, and operational efficiency • Collaborate with Data Engineers, Product Managers, and distributed engineering teams to deliver end-to-end ML solutions • Contribute to ML architecture decisions, experimentation approaches, and engineering best practices • Monitor, validate, and optimize ML model quality and forecasting performance in production environments • Produce technical documentation related to ML pipelines, models, and distributed systems • Mentor engineers and support technical growth within the team • Drive innovation in Machine Learning and AdTech technologies

• Own the research-to-production pipeline • Partner directly with research scientists to productionize new models • Build and extend the tooling and abstractions • Design and own model release gates • Optimize models and serving for production • Strengthen the build and delivery layer for models • Establish benchmarking and validation • Build the feedback loop