AI Specialist/Engineer

Há 4 dias


São Paulo, São Paulo, Brasil Data Meaning Tempo inteiro
Job Summary

We are seeking a highly skilled AI Specialist/Engineer to join our team at Data Meaning, a leading Business Intelligence and Data Analytics consulting firm. As a key member of our team, you will be responsible for designing, developing, and implementing AI solutions to drive business growth and improve operational efficiency.

Key Responsibilities
  1. AI Solution Development: Design and develop AI models and algorithms to solve complex business challenges, leveraging machine learning techniques such as supervised, unsupervised, and reinforcement learning.
  2. Collaboration and Communication: Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI-based solutions and ensure effective communication of technical concepts to non-technical stakeholders.
  3. Data Analysis and Insights: Analyze large datasets to extract meaningful insights and develop AI models for predictive analytics, driving strategic decision-making and business growth.
  4. AI System Deployment and Maintenance: Deploy AI models into production environments, ensuring scalability and performance, and continuously monitor AI systems to improve them based on performance metrics.
  5. Research and Development: Stay up-to-date with the latest AI trends and emerging technologies, driving innovation and applying new techniques to improve AI solutions.
  6. Documentation and Knowledge Sharing: Develop and maintain documentation for AI solutions and workflows, and provide technical support and guidance to junior team members on AI methodologies.
Requirements
  1. Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
  2. Experience: 3+ years of experience working with AI/ML frameworks, such as TensorFlow, PyTorch, Scikit-learn, and proficient in programming languages like Python, R, Java, or C++.
  3. Skills: Strong understanding of machine learning algorithms, neural networks, deep learning, and natural language processing (NLP), with experience in working with large-scale datasets, data pre-processing, and data visualization tools.
  4. Cloud Platforms: Familiarity with cloud platforms, such as AWS, Google Cloud, or Azure, for deploying AI solutions.
  5. Agile Environment: Ability to work in an agile environment and adapt to changing requirements, with excellent problem-solving skills and the ability to think analytically and critically.
  6. Communication: Strong communication skills, with the ability to explain AI concepts to non-technical stakeholders.
Preferred Skills
  1. AI Ethics and Bias Mitigation: Experience in AI ethics and bias mitigation.
  2. Reinforcement Learning and Computer Vision: Knowledge of reinforcement learning and computer vision.
  3. AI/ML Model Monitoring Tools: Experience with AI/ML model monitoring tools like MLflow or Kubeflow.
  4. AI Research and Publications: Contributions to AI research or publications in AI-related conferences.


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