Estamos em busca de um(a)
Data Scientist com foco em Inteligência Artificial (IA)
altamente qualificado para integrar nosso time de tecnologia, que queiram trabalhar conosco em um ambiente descontraído e animado, com aprendizado diário no desenvolvimento de grandes projetos, junto a grandes clientes pelo mundo.
Você vai projetar e implementar sistemas inteligentes utilizando técnicas clássicas e avançadas de Machine Learning (ML), atuando em colaboração com times multidisciplinares na exploração de dados, construção e avaliação de modelos, além da implantação de soluções baseadas em IA em ambientes de produção — desde plataformas em nuvem até dispositivos embarcados.
Oportunidade híbrida para Curitiba-PR e Sorocaba-SP, com presencial de 2 a 3 vezes por semana no escritório.
Inglês obrigatório.
Key Responsibilities
Design and develop AI-driven software systems using ML models
Use algorithms such as XGBoost, K-means, PCA, Neural Networks, GANs, Reinforcement Learning, LLMs, and more
Train, tune, evaluate, and document ML models using modern frameworks like TensorFlow, PyTorch, and Keras
Prepare models for deployment in different environments (cloud, on-premises, embedded devices)
Collaborate with development teams to integrate models into software architecture and data pipelines
Write technical reports and stay up to date with the latest AI/ML trends and technologies
Contribute to Agile ceremonies and sprint planning within a Scrum team
Required Qualifications
Advanced English (spoken and written, technical level)
Proven experience building, training, and validating ML and AI models
Solid experience handling complex and heterogeneous data (cleaning, deduplication, preparation)
Strong programming skills in Python (Scala, R, and PySpark are nice-to-haves)
Experience with AI libraries/frameworks: TensorFlow, PyTorch, Keras, Caffe, etc.
Solid foundation in algorithms, statistics, regression, decision trees, neural networks
Experience with time series, computer vision, and NLP
Familiarity with Data Lake environments: Hadoop ecosystem, Spark, Kafka
Experience with Microsoft Azure Cloud
Knowledge of automated testing and white-box testing
Nice to Have
Experience with LLMs (Large Language Models), federated learning, and GPU acceleration
Deployment of models in embedded or edge devices
Familiarity with MLOps practices and model lifecycle in production
Previous experience in international or distributed teams
Bonus points for
Experience with international teams/projects
Advanced English for reading and collaboration
Ability to work independently in remote/distributed environments
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