- Research, design, and implement state-of-the-art machine learning algorithms and models for image analysis and computer vision tasks.
- Develop and optimize deep learning architectures, including Convolutional Neural Networks (CNNs), for image recognition, object detection, segmentation, and other related tasks.
- Preprocess and augment large-scale image datasets to improve model performance and generalization.
- Collaborate with cross-functional teams to gather requirements, define project objectives, and deliver high-quality machine learning solutions.
- Evaluate and experiment with different techniques, frameworks, and tools to improve model accuracy and efficiency.
- Stay up to date with the latest advancements and trends in the field of image-based machine learning and computer vision.
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- Advanced English
- Solid understanding of machine learning fundamentals, including supervised and unsupervised learning, as well as deep learning techniques.
- Experience with image-based machine learning algorithms.
- Proficiency in programming languages such as Python, along with deep learning frameworks like TensorFlow, Keras, or PyTorch.
- Familiarity with popular CNN architectures (., VGG, ResNet, Inception) and hands-on experience in training and fine-tuning models.
- Proficient in data preprocessing, feature extraction, and augmentation techniques for image datasets.
- Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Excellent communication and teamwork skills
- Experience in deploying machine learning models in production environments.
- Knowledge of cloud platforms, such as AWS, Azure, or GCP, for scalable and distributed model training and deployment. Nossos principais benefícios
- Remuneração variável;
- Plano de Saúde;
- Plano Odontológico;
- Seguro de Vida;
- Previdência Privada;
- Benefício Ótica;
- Reembolso vacina;
- Universidade Corporativa;
- Gympass;
- Dependendo da unidade, você terá restaurante no local, vale refeição ou alimentação;
- Auxílio farmácia;
- Entre outros. Nosso Processo Seletivo A seleção começa com a sua inscrição, para algumas vagas, existem alguns testes adicionais. Você terá a possibilidade de conhecer pessoas do time nas entrevistas Nosso processo seletivo é flexível em termos de tempo, então não se preocupe Nossa equipe de Talent Acquisition está comprometida em proporcionar a melhor experiência para você. Analisamos todas as candidaturas cuidadosamente e fornecemos feedback em todas as etapas do processo. Além disso, todas as orientações serão enviadas por e-mail Sobre a John Deere A John Deere é líder global no fornecimento de produtos, tecnologia e serviços avançados para clientes que desempenham um papel essencial na agricultura, construção, florestal entre outros setores. Nosso objetivo é atender à crescente necessidade mundial de alimentos, combustível, abrigo e infraestrutura, enquanto promove a sustentabilidade e a preservação do planeta que chamamos de lar.Inovamos para impulsionar a produtividade e proteger nosso planeta e convidamos você a fazer parte dessa história. Trabalharemos juntos para criar, testar, superar para que para que a vida possa avançar.
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Computer Vision - Indaiatuba, Brasil - John Deere
Descrição
Reconhecemos e valorizamos a pluralidade dos nossos times. Por isso, criamos condições para a equidade de oportunidades através de políticas, práticas e atitudes que promovam uma cultura de respeito e o desenvolvimento de nossos talentos.Buscamos cada vez mais diversidade de gênero, etnias, religiões, LGBTQIAPN+, deficiências, culturas e histórias para nos ajudar em nosso propósito que é trabalhar para que a vida possa avançarEstamos sempre à procura de pessoas inovadoras que possam contribuir com a nossa missão. Que tal fazer parte do nosso time? Local Principal: Brasil (BR) - São Paulo - Indaiatuba Função: Engineering (CA) Título: Computer Vision & Machine Learning EngineerYour Responsibilities
What Skills You Need
What Will Make You Stand Out
